success stories in systems biology

SYSTEMSBIOLOGY

SUCCESSSTORIES IN

Project funded by the European Comission under the SeventhFramework Programme for Research and Technological Development

ContentsWelcome 2

Research 3

A model that gets to the heart of systems biology 3Denis Noble, Oxford University

Taking a systems-eye view of cancers in children 5Walter Kolch, Systems Biology Ireland

Systems biology study points to Turing model of finger formation 7James Sharpe, Centre for Genomic Regulation

Balancing flavour and texture in tomatoes - with systems biology 9Stuart Dunbar, Syngenta

Systems X.ch: Swiss bank on systems biology 11Daniel Vonder Muehll, SystemsX, Gisou van der Goot, EPF Lausanne, Cris Kuhlemeier, University of Bern

Answering big questions with a small bug 13Luis Serrano, Centre for Genomic Regulation

Blueprints for life 15Bas Teusink, Netherlands Platform for Systems Biology

Merrimack: Following a systems path to drug discovery 17Peter Sorger, Massachusetts Institute of Technology, and Birgit Schoeberl, Merrimack Pharmaceuticals

Beating the conundrum of variability in cardiac simulations 19Blanca Rodriguez, Oxford University

Stats and modelling – a Belgian diagnostic tool for arthritis 21Thibault Helleputte, DNAlytics

Virtual Liver Network: a collaborative solution to hepatic diseases 23Adriano Henney, Virtual Liver Network

Tools and Resources 25

SBML: A lingua franca for systems biology 25Michael Hucka, California Institute of Technology

Model Support: JWS Online and BioModels Database 27Jacky Snoep, Stellenbosch University, and Henning Hermjakob, European Bioinformatics Institute

SYSMic: An interdisciplinary skills course for biologists 29Gerold Baier and Geraint Thomas, University College London

COPASI: An open source software package easing the path to modelling 31Pedro Mendes, University of Manchester

SEEK and ye shall find data 33Katy Wolstencroft, University of Leiden

1 ISBE - www.isbe.eu

BIOGRAPHY

RIChaRd KITnEY ISPROfESSOR Of BIOMEdICaLSYSTEMS EnGInEERInG,ChaIRMan Of ThE InSTITuTEOf SYSTEMS and SYnThETICBIOLOGY and CO-dIRECTOROf ThE EPSRC naTIOnaLCEnTRE fOR SYnThETICBIOLOGY and InnOvaTIOn aTIMPERIaL COLLEGE LOndOn.

Kitney is a leading researcher inthe field of synthetic biologyand, with Professor PaulFreemont, has beenresponsible for developing theUK National Centre forSynthetic Biology - which isnow recognised as one of theleading international centres inthe field.

In June 2001, Professor Kitneywas awarded the Order of theBritish Empire (OBE) in theQueen's Birthday Honours Listfor services to InformationTechnology in Healthcare.

WelcomeI am very pleased to introduce this collection of success stories in systems biology, produced aspart of the Infrastructure for Systems Biology Europe (ISBE) project and funded through theEuropean Union Seventh Framework Programme. This is just a small sample of the cutting edgeresearch being carried out in systems biology in academic, clinical and industrial settings which ismaking an increasingly significant impact as we seek to tackle grand societal challenges in areasas diverse as health, agriculture and biotechnology.

In the past fifteen years, systems biology research has become embedded across a range ofbiological and biomedical fields. This has been driven by the growing abundance and complexity oflarge biological data sets, the development of tools and techniques with which to performcomprehensive, genome-wide analyses, and the capacity to share these via high speed connectionsbetween disparate research groups and disciplines. Using a systems approach, life scientists arenow able, for the first time, to study the complex and dynamic interplay between the componentsof a system (be it at the level of a cell, tissue, organ, organism or population). This can now gobeyond understanding function, to enable intervention in the behaviour of the system in a predictiveand rational manner. The stories told in this publication illustrate the breadth of work going on inthis dynamic area.

Challenges remain, however: how to increase access to modelling, developing workable standardsthat enable the effective reuse of data and models as well as training new generations of scientistsin this multidisciplinary approach. A number of the tools and resources featured in this collectionhave been developed to address individual bottlenecks but an integrated infrastructure for systemsbiology is needed if we are truly to exploit the potential of systems biology. From 2012-2015, theISBE consortium of 23 partners from 11 EU member states has been working with the academic,clinical and industrial research communities to develop plans for a systems biology infrastructurethat will address these challenges with services that support a range of users, from novices toexperts, from SMEs to Big Pharma, from university labs to hospital clinics. Our proposals for theinfrastructure’s development over the coming years have been published in a business plan (July2015) and the roll out of preliminary services is due to commence in late 2015.

I would like to thank my colleagues from academia and industry who gave up their time for thiscollection. They have given a fascinating insight into the iterative research process that is the basisof systems biology, the cycle of experimentation and computational modelling that harnesses thepotential of ‘big data’ and turns it into tangible outcomes for society.

Yours Prof. Richard I Kitney, OBE FREngCoordinator, Infrastructure for Systems Biology EuropeImperial College London

ISBE - www.isbe.eu 2

PROF. DENIS NOBLE DISCUSSES THE DEVELOPMENT OF HIS WORK IN CARDIAC CELLMODELLING FROM 1960 TO THE PRESENT

Your heart: without it, you wouldn’t survivevery long. So medicine strives to keep it healthyand fix it if something goes wrong. Yet theheart’s central role in our bodies can also makeit difficult to test out new clinical approaches inhumans. One way to get around this is to builda mathematical model that predicts how theheart will behave, and today the ‘virtual heart’approach is helping to make drug discovery andtesting safer.

The heart model has its origins in 1960, and itsgrowth since then exemplifies the systemsbiology approach of using modelling andexperimental data to enable new insights. Itbegan when Denis Noble and his PhDsupervisor Otto Hutter worked with hearttissue at University College London. They wereinterested in a type of electrical ‘gate’ in heartcells called the potassium channel, and Noblewanted to develop a mathematical model ofthe heart to explore its actions.

He based his work on a 1952 mathematicalmodel that described the characteristics ofexcitable cells, and to build up the model Noblemanaged to wrangle some time on the FerrantiMercury Computer in London. He sat in onmaths lectures to get up to speed with the

formulae and spent late nights punching inmachine code in his allotted time between 2and 4am.

Soon his work paid off and the heart modelbegan to work. “It didn’t take too long to get tothe point where rhythm was coming out of theequations,” recalls Prof. Noble, who is today anEmeritus Professor at Oxford University andPresident of the International Union ofPhysiological Sciences. Papers in theprestigious journal Nature followed swiftly, andsince then the heart model and experimentaldata have closely intertwined, building up ourknowledge of how this key organ works.

In some cases, the model has informed theexperiments - Noble recalls how in the early1960s his model put paid to a method of usingdouble probes to stimulate heart tissue in thelab: the maths clearly showed that theexperimental approach was disrupting heartcell function. In other cases, experimentalfindings enhanced the model. “By about 1967,the existence of calcium channels had beendemonstrated, and that was the first point atwhich it was obvious that the model wouldhave to be expanded,” says Prof. Noble. “Thatprocess of expanding and taking more andmore into account has gone on ever since.”

In the decades since he punched machine codeinto the Mercury, Prof. Noble has worked withcollaborators around the world to build up theheart model and shed new light on how ionchannels work. Meanwhile, computertechnology grew too, enabling moresophisticated modelling and the developmentof a virtual organ. The growth of the heart

DENIS NOBLE IS A BRITISHBIOLOGIST WHO WAS THEFIRST TO MODEL CARDIACCELLS, DETAILED IN TWOPAPERS IN NATURE IN 1960. HEWAS EDUCATED AT UNIVERSITYCOLLEGE LONDON AND MOVEDTO OXFORD IN 1963 ASFELLOW AND TUTOR INPHYSIOLOGY AT BALLIOLCOLLEGE. FROM 1984 TO 2004,HE HELD THE BURDONSANDERSON CHAIR OFCARDIOVASCULAR PHYSIOLOGYAT OXFORD UNIVERSITY.

He is now Professor Emeritusand co-Director ofComputational Physiology. Hisresearch focuses on usingcomputer models of biologicalorgans and organ systems tointerpret function from themolecular level to the wholeorganism.

Middle out means that you start at one level - which mightbe in the middle, in our case it’sthe cell. Then you reach down

to individual molecules and youreach up to the organ.

BIOGRAPHY


model exemplifies the ‘middle-out’ approachthat Prof. Noble has long supported. “Middleout means that you start at one level - whichmight be in the middle, in our case it’s the cell,”he explains. “Then you reach down to individualmolecules and you reach up to the organ.”

The mathematical approach can also offer asafe and ethical support to look for newmedications and anticipate side-effects, saysProf. Noble, explaining how in one case theheart model showed in the late 1970s thatblocking a newly discovered ion channel wouldhave interesting clinical effects. “We were ableto show that a blocker of this mechanismwould not stop the heart, that it would slow it,”he says. “So a pharmaceutical company lookedfor and found a compound that did that, and itis now out there as an approved drug -ivabradine.”

In another case the heart model helped toexplain the dual-action effects of a compoundcalled ranolazine, explains Prof. Noble. “Weused computation to show why itscombination of actions would be expected tobe synergistic,” he says. “And that provideddata about the drug as it went throughregulatory approval.”

He now sees potential for the virtual heart tocontinue informing drug discovery andregulation, thereby reducing risks in drugdevelopment. “Many side effects of drugs hitthe heart and cause arrhythmia, that has in thepast been the cause of withdrawal of drugs,”he says. “And many of the companies have gotout of this kind of work, it’s too risky so we arelooking to see if you can use the model to filterat an early stage synergistic actions ofpotential drugs. Getting it right in the earlystages [of drug discovery and development] isa good idea, and this is where the model canhelp.”

Words: Claire O’ConnellJanuary 2014

further InformationDenis Noble’s website www.musicoflife.co.uk

We used computation to showwhy ranolazine’s combination

of actions would be expected tobe synergistic and that provideddata about the drug as it wentthrough regulatory approval.

CuRREnTdEvELOPMEnTSIn CaRdIaC CELLMOdELLInG

Premature heartbeats explainedas a change in the stabilityproperties of the dynamicalsystem of the heart cell duringthe course of an action potential(Tran et al., 2009).

Tissue electromechanics modelsshow how infarctions can causearrhythmia.

Multiscale models ofelectrophysiology illustrate howcellular action potentials giverise to the electrocardiogram(ECG) measured macroscopicallyon the surface of the body(Sundnes et al., 2006).

Multiscale, multiphysics modelscan account for the effects ofgenetic mutations at levels fromion-channel structure, function,and macroscopic current; cell,tissue and organ function


WALTER KOLCH ON A EUROPEAN PROJECT THAT IS TACKLING PAEDIATRICTUMOURS USING SYSTEMS BIOLOGY

ASSET IS A 14 PARTNERCOLLABORATIVE EUROPEANFP7-HEALTH-2010 PROJECT INTHE THEME ‘TACKLING HUMANDISEASES THROUGH SYSTEMSBIOLOGY APPROACHES’. USING ACOMBINATION OF STATE-OF-THE-ART GENOMICS,PROTEOMICS ANDMATHEMATICAL MODELLING,ASSET’S MAJOR GOAL IS TOIDENTIFIY MECHANISTICALLYUNDERSTOOD NETWORK VUL-NERABILITIES THAT CAN BEEXPLOITED FOR NEWAPPROACHES TO THEDIAGNOSIS AND TREATMENT OFHIGHLY AGGRESSIVE ANDDEVASTATING PAEDIATRICTUMOURS.

Prof. Walter Kolch is director ofSystems Biology Ireland and theConway Institute of Biomolecularand Biomedical Research inUniversity College Dublin. In thelast ten years, Prof. Kolch hasbuilt an international reputationacross three areas: MAPKsignalling, proteomics, and cancerresearch, especially in regard tousing systems biologyapproaches.


BIOGRAPHY

Cancer is never welcome, but when it arises inchildren it seems all the more unfair. The EU-funded ASSET (Analysing and Striking theSensitivities of Embryonal Tumours) project istaking a systems biology approach to figuringout the most useful treatments for a range ofpaediatric tumours (neuroblastoma, medul-loblastoma and Ewing’s sarcoma), and they arediscovering new ways of investigating thediseases.

A major focus within the consortium isneuroblastoma, explains ASSET co-ordinatorProfessor Walter Kolch, who is Director ofSystems Biology Ireland (SBI) at UniversityCollege Dublin. Contrary to what the tumour’sname might suggest, “neuroblastoma does notarise in the brain but in the belly,” he explains.“It is a tumour of the peripheral sympatheticnervous system.”

Accounting for about 15% of all childhoodcancers, neuroblastoma strikes during infancyor toddler years and presents in a variety offorms - some tumours are aggressive andpotentially rapidly lethal, while other tumourswill eventually disappear even if they havespread throughout the body (metastasised)and even if there is no treatment. “It can beextremely aggressive and kill the child in a fewmonths, or else it is the only tumour knownwhich spontaneously regress even though ithas metastasised,” explains Professor Kolch.“So in this case a metastatic tumour can goaway without any treatment.”

Aggressive treatment for cancer is not onlyharsh for the child, but it could potentially havelonger term effects on their health. So ifclinicians can tell from the outset whether aneuroblastoma is aggressive or likely to resolveon its own, the therapy could be targeted at thechildren who would benefit from it, while thosewhose tumours who don’t need treatment willbe spared the need to go through it.

But how can you tell? Taking a systems biologyapproach, the 14-partner ASSET consortiumhas found that molecular signals in the tumourcells can yield important information. Theirwork centres on a biochemical signallingpathway called ‘JNK’, which is activated todiffering levels in the tumour cells.

“JNK can make the neuroblastoma cells die orlive depending on the exact activation kinetics,”explains Professor Kolch. “If the pathway isactivated very slowly then the cells survive andgrow, but if it is activated steeply like a switch,the tumour cells die - and that is a good thing.”Using a mix of experimental measurementsand computational modelling, the ASSETscientists have been able to assess theaggressiveness of the tumour cells. “By

JNK can make theneuroblastoma cells die orlive depending on the exact

activation kinetics

developing a computational model of theactivation network we could see which of thenodes control it,” says Professor Kolch. “Thenin individual patients we can measure thesethree or four protein concentrations and wecan adjust this model for each patientindividually. Using this approach we haveshown we can assess each patient’s tumourfor likely aggressiveness.”

The project is also using computationalmodelling to look for new treatments, he adds,by simulating the effects of drug combinationson the key biochemical pathways.

“At the moment neuroblastoma is treatedmainly with drugs that damage DNA andthereby cause JNK to be activated,” explainsProfessor Kolch. “But we are looking at howusing combinations of existing drugs couldactivate JNK more specifically, without causingthe problematic DNA damage. We have madevery good progress in identifying potentialcombinations, and some of these agents arealready in clinical use so there is the hope thatany new combinations we find could betranslated into the clinic fairly quickly.”

The ASSET consortium is making progress toowith a systems biology approach to thepaediatric brain tumour medulloblastoma andto Ewing’s sarcoma, notes Professor Kolch.“We have found better ways to stratifypatients across the different types of cancer,”he says.

And now the obvious route for translatingfindings is through the clinical research groupsin France, Germany and Switzerland who areinvolved in the project.

“These clinical groups are doing clinical studiesall the time and can conduct trials to see howto most effectively implement the discoveriesthat come through our systems biologyapproach,” notes Professor Kolch. “This is thebest and most direct way to bring what we arefinding into the clinic.”

Words: Claire O'Connell June 2015

further InformationASSETwww.ucd.ie/sbi/assetSystems Biology Irelandwww.ucd.ie/sbi

We have found better ways to stratify patients

across the different typesof cancer

how do tumours form?From an academic standpointchildhood tumours offer arelatively ‘pure’ model to studyhow cancers arise, because theperson has had less time todevelop non-cancerous DNAmutations.

By analysing molecular charac-teristics of a childhood cancercalled neuroblastoma, Prof.Walter Kolch and colleagues inthe ASSET project have foundthat there are many ways forsuch tumours to arise at thelevel of DNA, but that the effectson cell signalling are less varied.“It tells you if you look at theeffects of these mutations theyare rather similar so you need totarget the effects rather thanthe cause,” he says.

Genetically modifiedzebrafish were used in theproject to evaluate potentialneuroblastoma drugs

Researchers from University College Dublin analysing results


YOU SEE THEM EVERY DAY, BUT HAVE YOU EVER STOPPED TO WONDER HOW YOURFINGERS ‘KNEW’ TO BECOME FINGERS WHEN YOU WERE A DEVELOPING EMBRYO?

It’s a puzzle that has had scientists scratchingtheir heads for decades, but a recent study ledby Dr James Sharpe at the Centre for GenomicRegulation in Barcelona has pointed out how amolecular system controls the process.

Dr Sharpe’s lab is interested in how cells andtissues interact to build organs and body parts,and the limb has a strong track record inresearch on how it organises itself. “The realityis that for any organ we probably know just thetip of the iceberg, but for the limb we havemore of that tip of the iceberg than for theothers,” he says.

To dig deeper into the networks of cellular andmolecular interactions that underpin limbdevelopment, Dr Sharpe uses a systemsapproach, linking computer models withexperimental results. “The developing limbinvolves hundreds of thousands of cellscommunicating with each other, movingaround and making decisions to becomemuscle cells or bone cells,” he says. “So weexamine that using a back-and-forth, iterativeapproach, where we use computer modellingalongside experimental and molecular science.”One of the lab’s most recent successes,published in Science in 2014, has shed light onfingers. During embryonic development inanimals with backbones and arms, fingersform when a flat plate of tissue grows out atthe end of the miniature limb, and cells then dieaway in a pattern to form spaces and chisel outthe digits.

“At that very early stage, when the hand isforming, the individual cells within that plate oftissue have not yet decided whether they aregoing to make a finger or an interdigit,” explainsDr Sharpe, who co-ordinates the EMBL-CRGSystems Biology Unit.

His lab examined the process underlying thatcellular decision using a mouse model wherecells have been transgenically engineered toproduce the fluorescently glowing protein GFPif they are choosing the digit fate (where theSox9 gene is expressed) rather than the inter-digital fate.

This approach allowed them to sort the cellsinto two groups during the six-to-ten hourwindow when the cells are making this criticalcell-fate choice: those about to make fingers,and those about to become interdigital.

JAMES SHARPE IS AN ICREA(INSTITUCIÓ CATALANA DERECERCA I ESTUDIS AVANÇATS)RESEARCH PROFESSOR ANDALSO THE LEADER OF THESYSTEMS ANALYSIS OFDEVELOPMENT GROUP AT THECENTRE FOR GENOMICREGULATION (CRG),BARCELONA.

The goal of his research group isto focus on the development ofthe vertebrate limb, both at thelevel of gene regulatorynetworks, and of the physicalinteractions between cells andtissues. To achieve this, thegroup includes embryologists,computer scientists, imagingspecialists and engineers.

BIOGRAPHY

We examine the developing limb using a

back-and-forth, iterativeapproach, where we use

computer modellingalongside experimental and

molecular science.


By examining the networks of genes that wereactive in these distinct populations of cells, theresearchers identified two key signallingpathways - BMP and WNT – that were moststrongly involved in the decision about‘fingerness’ or ‘gapness’. “This analysis of geneexpression was complemented by examinationof the proposed pathways at the proteinactivity level, which also supported theconclusions,” says Dr Sharpe.

Once enough molecular data had beengathered, the Barcelona lab began constructionof a computer model to explore a system ofdevelopment proposed by British computingpioneer Alan Turing, where chemicals reactwith each other and diffuse over space tocreate particular types of stripy or spottypatterns.

“The computer model was essential, becauseTuring systems are very non-intuitive,” says DrSharpe. “But our initial step of screening for themolecular components was also key: if themodel had been abstract – not based on dataabout real molecules involved – it would beunable to make predictions that we couldexperimentally test in the lab.”

The researchers turned the BMP and WNTsignalling up and down – both in the computermodel and in in-vitro experiments – andwatched what happened. When they switchedoff the BMP pathway all the cells became gaps.If they repressed the WNT pathway instead, allof the cells became fingers. And repressingboth the BMP and WNT pathways at the sametime but to different degrees rearranged thepattern into fewer, fatter fingers.

“The most exciting thing was that we got thesame result in the computer simulation and inthe real experiments. This interplay betweenthe modelling and experimentation is at theheart of the systems biology approach, and itis the strongest proof we have that thesemolecules are part of a Turing system,” says DrSharpe. “For decades this idea was activelyresisted, but our results provide good evidencefor it, and we think this Turing mechanismpossibly goes back all the way into fish, eventhough the number of digit structures theyhave is not the same.”

Figuring out fingers is just one aspect ofunderstanding limb development, and DrSharpe’s lab is also using systems biology toexamine how a limb as a whole organises itselfto form a humerus, ulna and radius, wristbones and - finally - fingers.

Understanding such aspects of limbdevelopment should also help to inform thewider field of regenerative biology and tissueengineering. “To be able to heal and maybe oneday to even build multi-cellular tissues, weought really to understand how multicellulartissues build themselves in the first place, andwe still have a lot to learn about that,” says DrSharpe.

“Our view is that a systems biology approachwill ultimately be the only way to explain,understand and then engineer livingmulticellular tissues, either tissues in dish thatcan then be put back into patients, or bystimulating patients’ own tissues to heal andregenerate.”

Words: Claire O’ConnellMay 2015

further InformationCentre for Genomic Regulation crg.es

Patterns in biology –the Turing connection

In August 1952, Britishcomputing pioneer Alan Turingpublished a seminal paperentitled The Chemical Basis ofMorphogenesis.

It outlined how just two distinctmolecules (‘morphogens’) couldunderpin the spontaneousdevelopment of spotted andstripy patterns by diffusing andinteracting in specific ways toform repetitive motifs.

Turing died two years after thepaper was published inPhilosophical Transactions B, butthe reaction-diffusion model itdescribed has since beenproposed to underpin numerousrepetitive patterns in nature,including the stripes on a zebra,and now the more subtlepatterns of digit formation.

The most exciting thingwas that we got the same

result in the computersimulation and in the real

experiments.


STUART JOHN DUNBAR ON A COLLABORATION BETWEEN SYNGENTA AND IMPERIAL COLLEGE LONDON THAT IS PROVING FRUITFUL

When you choose tomatoes at the market,what do you look for? Firm, crisp texture? A ripeproduct that will tantalise the tastebuds withits strong flavour? Or what if you could haveboth firmness and that ripe taste?

A project between Syngenta and ImperialCollege London is using systems biology toexamine the interplay of factors thatdetermine flavour during ripening of this majorfruit crop, and its findings are informingbreeding programmes to develop new varietieswith a satisfying ripe flavour while the productis still crisp.

Food producers and retailers want to sell asmuch of their fare as possible, but consumershave their preferences - and for many thatmeans turning up their noses at more ‘squidgy’tomatoes, explains Dr Stuart John Dunbar,Head of Bioscience at the global agribusinesscompany Syngenta.

“If you buy a tomato from supermarket, ittastes more tomatoey and nicer the riper it isand therefore the squidgier it is, but squidgytomatoes are not good for supermarkets,” hesays. “In northern Europe and in the UnitedStates in particular, shoppers want tastytomatoes but they want a nice, crisp texture,they won’t tend to buy soft tomatoes.”

But how do you match those requirements? Aproject at the Syngenta Innovation Centre onSystems Biology at Imperial College London(the University Innovation Centre, or UIC) hasbeen building a predictive model of tomatoripening and fruit quality to get a better

understanding of the biochemical and genetic‘control points’ of key features such as textureand flavour.

“We are interested in detecting molecularmarkers in the tomato ripening pathways thatgrow flavour, and ultimately could we bring theflavour components of ripening earlier into theripening process,” explains Stuart, who is anadjunct professor of cellular and molecularbiology at Imperial.

SYNGENTA IS A WORLD-LEADING AGRI-BUSINESSCOMMITTED TO SUSTAINABLEAGRICULTURE THROUGHINNOVATIVE RESEARCH ANDTECHNOLOGY. THE COMPANYEMPLOYS 28,000 PEOPLE INOVER 90 COUNTRIES WITH APURPOSE OF BRINGING PLANTPOTENTIAL TO LIFE.

Prof. Stuart John Dunbar is Headof Bioscience at Syngenta andproject leader of the UniversityInnovation Centre on SystemsBiology at Imperial CollegeLondon. Stuart is also an AdjunctProfessor of Cellular andMolecular Sciences at Imperial.

BIOGRAPHY

It would have been impossibleto analyse the datasets using

conventional biochemicalapproaches, so we took a

systems approach where wetried to integrate complexity

and find the answers.

Stuart at a public outreach event at Imperial College London, 2013


The project focused on four isogenic lines fromthe Ailsa Craig variety of tomato where thelines have been bred to inhibit components ofthe ripening process. “We have genomic andbiochemical information on these tomatoes,and the tomatoes fit a range of components onthe ripening and flavour pathways - they arerepresentative of different types of outcomes,”explains Stuart, citing the example of one,Never Ripe. “It does what it says on the tin - itnever gets ripe.”

The work, led by Dr Charlie Baxter fromSyngenta, used systems biology to model thebiochemistry and the metabolic profile of thesefour isogenic lines, and the enormity of thattask meant a systems biology approach was needed, explains Stuart. “It would have beenimpossible to analyse the datasets usingconventional biochemical approaches, so wetook a systems approach where we tried tointegrate complexity and find the answers.”

The project used machine learning (wheresoftware carries out actions that have not beenspecifically pre-programmed) thanks toProfessor Stephen Muggleton’s team atImperial, and this offered an unbiasedapproach to tackling the questions, accordingto Stuart: “It is a way of addressing problemswithout having to predefine what the problemwas, so it is an unbiased way of addressing thecomplexity.”

The project successfully modelled andintegrated data from the tomato lines aboutgene expression and metabolism, and severallearnings emerged, including the value ofsystems biology and machine learning in thiscontext.

“It has told us how you can cross data gaps andhow big those data gaps can be, and it told usabout the nature of the data that you need -

the data gaps that we can reliably bridge arequite small, which was an interesting outcome,but the positive thing was that you need lessdata than we thought,” says Stuart.

Molecular markers identified in the UIC projectare now being brought forward and used in abreeding programme, but Stuart cautions thereare no guarantees yet that retailers andconsumers will ultimately get the holy grail ofa firm and ripe-tasting tomato.

“The project furthered our understanding ofthe complex pathways involved in fruit ripeningand has allowed us to focus on specific aspectsfor further analysis and marker development,”explains Stuart. “It takes a long time to breed anew variety so we will see the fruits of ourlabour only after 6 years or so!”

Words: Claire O’Connell May 2015

further InformationSyngentawww.syngenta.comSyngenta Centre on Systems Biology at Imperial College Londonwww3.imperial.ac.uk/syngenta-uic

The project has successfullymodelled and integrated

data from the tomato linesabout gene expression and

metabolism

a systems approachto ecosystems

How does crop growthaffect biodiversity andfood webs? Research atthe Syngenta InnovationCentre on SystemsBiology at ImperialCollege London using asystems biologyapproach to model thepotential impact of cropson biodiversity, and sofar the project has beenextremely successful,according to Dr StuartJohn Dunbar, Head ofBioscience at Syngenta.

“It has showed that wecan predict food websand the impacts ofdifferent types ofcropping systems onbiodiversity,” he says. “Itis helping us with ourwhole biodiversityagenda andunderstanding theimpacts on ecosystemservices.”


NATIONAL INITIATIVE IS PUTTING SWISS SYSTEMS BIOLOGY ON THE MAP

Switzerland is an independent state used tostriking out on its own path. In this vein, theSwiss launched an initiative in 2008 to fundand promote systems biology to fireSwitzerland into the vanguard of an emergingfield.

"There's been a paradigm shift fromreductionist molecular biology to a holisticsystems biology approach, and Switzerlanddecided to support this new era by providingfunding," explains Daniel Vonder Müehll,Managing Director of the initiative,SystemsX.ch. Encouragement also came frombig pharma firms like Roche and Novartis.

The initiative now gels together 15 equalinstitutional partners from academia andindustry which provide matching funds to theinitiative, overseen by the Swiss NationalScience Foundation. Over 1,000 scientists arecurrently involved in SystemsX.ch projects. Butalso remarkable is the multidisciplinary natureof the projects forged and advances achieved.

The aim of systems biology and, hence, ofSystemsX.ch concerns understandingprocesses and the dynamics of biologicalsystems and relies on extensive quantitativedata and modelling.

One of the earliest consortiums and at thesame time the largest project withinSystemsX.ch is LipidX, setting forth in 2008 toexplore the world of lipids; though majorbuilding blocks of cells, lipids have beenneglected in the ‘-omics’ era. They are difficultto study and do not conform well to areductionist beat. "You can purify a protein. Butlipids are much smaller molecules and they

generally assemble into higher orderstructures such as membranes, rather thanstaying as individual entities. Therefore itmakes little sense to study them in isolation,"says Gisou van der Goot of EPF Lausanne, leadinvestigator for the project, now in its secondphase.

The consortium just published the firstdatabase that provides knowledge on lipids. Italso took initial steps to getting to grips withhow the nutrient state of cells andenvironment affects lipid composition, and theinfluence of lipids on cells. “Before this projectnone of us were actually doing lipidomics andthinking in a systems way about lipids.SystemsX made this possible and changed theway we tackle the problem,” van der Gootexplains.

The entire initiative sped up the adoption oftechnologies and quantitative approaches inexperimental labs. Questions in systemsbiology require a symphony of analyses in thelab and computer modelling, which itselfdemands input from biology, maths, physics,chemistry, computer science, informatics,engineering and medicine.

Daniel VonderMüehll isManagingDirector ofSystemsX.ch andleads theManagement

Office responsible for theexecutive work of the systemsbiology initiative. Previously hewas Head of ResearchManagement at University ofBasel and Head of PermafrostMonitoring Switzerland.

F. Gisou van derGoot is aprofessor at theEcolePolytechniqueFédérale de

Lausanne, Switzerland. From thestudy of the interaction ofbacterial pathogens with targetcells to her work on proteinpalmitoylation, van der Goot isinterested in how theorganisation of cellularmembranes allows precise andefficient communication.

Cris Kuhlemeier ishead of theInstitute of PlantSciences,University ofBern. The

Institute carries out research inplant development, molecularplant physiology, plant nutrition,plant ecology, vegetation Ecologyand palaeoecology

BIOGRAPHY

There's been a paradigmshift from a reductionist

molecular biology to aholistic systems biology

approach, and Switzerlanddecided to support this new

era by providing funding


It is not plain sailing. “It’s a real challenge. Youcan talk but it doesn’t mean that other peoplelisten,” observes van der Goot, speaking of thechallenges of interdisciplinary communication.“It took time, but was worth the effort.” Plantscientist Cris Kuhlemeier at the University ofBern says the first four years saw theconsortium he leads “mostly trying to get tounderstand each other.” The SystemsX.chproject PlantGrowth2 is now “really anintegrated group of people,” he says proudly.

Crops in recent years have been scrutiniseddown the lens of genetics, but little is knownabout the mechanics of growth. “DNA is alinear code, but how do you go from that to a3D shape. Maybe 20 years ago people weretotally focused on chemical signalling, but nowwe are trying to explain morphogenesis also interms of physics” says Kuhlemeier, who hasstudied a mysterious, truly quantitativeproblem for two decades: why leaves spiralpredictably around stems according to theFibonacci sequence, with the next leaf alwaysdisplaced by 137 degrees.

“This is a quantitative problem. You cannotsolve it only with genetics. There are notranscription factors that specify angles. Wehad to resort to modelling. I joined forces witha computational scientist and we produced thefirst mathematical model of a developmentproblem in plant biology,” Kuhlemeier recalls.But the PlantGrowth2 project is not solelyconcerned with theory: it aims to tackle a real-world problem: hunger. The consortiuminvestigates teff, the staple crop in the Horn ofAfrica, in an effort to improve yield and stop itfalling over (lodging) in wind and rain – causinglosses of 35-50%. They have used quantitativemethods and modelling to circle weak pointsand develop better varieties.

Micro-machinery was devised to measure cellwall strength at different places. Kuhlemeier’sbiology postdoc Sarah Robinson has beguntaking on hard core physics courses, while acomputational scientist colleague hasimpressed him with how much biology he

picked up. A highpoint has been the creation ofnew imaging technology called MorphoGraphX,published in May 2015 in eLife, which makes itpossible to segment cells and follow theirdeformation over time in 3D. Uses includeshape extraction, growth analysis, signalquantification and protein localisation.

Vonder Müehll recalls the first years of theinitiative, when projects were strong on datacollection, but not accomplished in systemsbiology. “Scientists are human and most stayin their comfort zone if possible, so you needclear incentives,” he says. In the second phase,which began in 2013, SystemsX.ch redirectedmore emphasis on theoretical work,simulations and modelling.

The next big event is the ‘All SystemsX.ch Day’to be held in Berne on September 15th 2015,a big meet and greet networking opportunity,accompanied by talks and panel discussions.

The Swiss initiative ends in 2018, with nofollow up: the Swiss are confident that theyhave opened a path that researchers willwillingly follow, assisted by multidisciplinaryalliances and greater comfort in striking out ona systems biology route. That’s one expectedreturn on investment.

Words: Anthony King May 2015

SystemX changed the way we tackled

the problem

SystemsX.ch faCT fILE

SystemsX.ch is the largestever public research initiativein Switzerland. It focusesspecifically on a broad topicalarea of basic research,systems biology. Initially, over120 million Swiss francs werecommitted to the initiative,with its first stage runningfrom 2008 to 2012.

A further 100 million francswas committed forconsolidation over the period2013 to 2016. A slightreadjustment in the secondstage saw promotion of moretheory, simulations andmodelling projects. In addition,a special round invited forapplications of MedicalResearch and Developmentprojects, with medical andclinical parts. Projects coveringtopics such as prions, HIV,metastasis, melanoma andinflammatory bowel diseasewon funding.

Today, SystemsX.ch supportsaround 220 projects, morethan 1,000 scientists andalmost 400 research groups.


further InformationSystemsXwww.systemsx.ch LipidXwww.systemsx.ch/projects/research-technology-and-development-projects/lipidx/PlantGrowth2wiki.systemsx.ch/display/PGRTDproj/Plant+Growth+Home

LUIS SERRANO FROM THE CENTRE FOR GENOMIC REGULATION IN BARCELONA EXPLAINSHOW HIS RESEARCH ON A SMALL BACTERIUM CAN HELP US TO UNDERSTAND OTHERLIVING SYSTEMS AND HOW IT CAUSES DISEASE

THE CENTRE FOR GENOMICREGULATION IN BARCELONA ISAN INTERNATIONALBIOMEDICAL RESEARCHINSTITUTE OF EXCELLENCEWHOSE MISSION IS TODISCOVER AND ADVANCEKNOWLEDGE FOR THE BENEFITOF SOCIETY, PUBLIC HEALTHAND ECONOMIC PROSPERITY.

Dr Luis Serrano is Director ofCRG and leads the Design ofBiological Systems researchgroup. The group works towarda quantitative understanding ofbiological systems to an extentthat one is able to predictsystemic features, with thehope to rationally design andmodify their behaviour.

Given enough technology and know-how,could we completely understand how an entireliving system works? It’s an ambitioussuggestion, but Dr Luis Serrano and colleaguesat the Centre for Genomic Regulation inBarcelona are in the process of finding out.

Living organisms vary hugely in size andcomplexity, so the researchers in Barcelonahave chosen their focus wisely: a smallbacterium called Mycoplasma pneumoniae, asingle cell organism that has a relatively simplemetabolism.

The microbe is of clinical relevance because itcan cause atypical pneumonia in humans,explains Dr Serrano, but the main reason forselecting it as a model organism is itsmanageable size.

”It is one of the smallest bacteria you can growin the lab,” he says. “And the whole idea of theproject has been to ask if you have enoughresults and enough money and enough know-how would you fully understand a livingsystem.”

To find out more about M. pneumoniae DrSerrano’s group and collaborators at theEuropean Molecular Biology Laboratory have

been analysing the main biochemicalcomponents of the bacterial cell, how theyrespond under different conditions and howthe components fit together to form afunctioning system.

Much like a car, a cell has various componentsthat need to work both in their own right andtogether for the system - or car - to work. Inthe car, an engine, gears and wheels functionindividually and together to make the car go. Ina cell, molecular systems involving DNA, RNA,proteins and sugars work in synchrony to runthe living system, and Dr Serrano has beenlooking at these systems.

”We acquire the relevant data from the cell -we are looking at its metabolism, itstranscriptome [RNA], the proteome [proteinsin the cell],” he says. “But we are not looking atevery protein individually, we try to get thewhole picture: so we are not looking at everyscrew in the car, we are looking at the maincomponents.”

By perturbing the cells and seeing how eachsystem reacts, Dr Serrano and co-workershave been bringing a larger picture into focusof how the system as a whole responds tochanges in its environment.

”We explore how it responds to factors likeexposure to drugs, changes in temperature orchanges in nutrients,” he says. “Our approachis a little like if you wanted to analyse thenervous system of the human you could applysomething very hot and if the person jumpsthen the nervous system has responded.”

If you have enough results and enough money and

enough know-how, would you fully understand a

living system?

BIOGRAPHY


COMPLICaTIOnSaSSOCIaTEd WIThMYCOPLASMAPNEUMONIAE

Lobar consolidation Abscess Bronchiolitis obliterans Necrotizing pneumonitis Acute respiratory distress syndrome Respiratory failure

Design of Biological Systems Group, 2013

Mycoplasma pneumoniae

One of the biggest findings to emerge is thatM. pneumoniae has sophisticated mechanismsfor controlling how its genes are expressed.

The microbe has two systems of ‘methylation’- a form of tagging on DNA that can determinewhether genes are switched on or silenced.“We know the bacterium has very strongmethylation and there are two systems, one isgeneral, and there is another more specificsystem that we don’t know what it is doing,”says Dr Serrano.

In addition, the small bacterium contains arelatively large amount of ‘non-coding RNA’, anobservation that has now also been made inmore complex bacteria as well as in eukaryoticcells, which are the types of cells that make upplants and animals.

”It looks now like bacteria have as large aproportion of non-coding RNA as eukaryotes,”says Dr Serrano. ”I think this is something thatis characteristic of all branches of life.”

The team also saw that the cell can readstretches of its DNA either classically or in a‘staircase’ pattern - once more this was asurprise to see in the tiny cell, notes DrSerrano, and the phenomenon has since beenobserved in other species of bacteria too.

The big challenge is now to integrate the largevolumes of data from the tiny Mycoplasma andto sift out the signal from the noise.

”We have been looking at proteomics, tran-scriptomics, chemogenomics, everything,” saysDr Serrano. “And now we want to put ittogether in a way that makes sense. So we aretrying to integrate everything into a big modelbut this is not easy. You might find 100 proteinsacetylated or 60 proteins phosphorylated -how much of this is noise and how much isbiologically significant? Which ones are really

doing something and which ones are justpassing by?”

In the longer term, having such insights intothe bacterium could help to understand how itcauses disease, and it may also offer routes toengineer the microbe as a drug-deliveryplatform to bring medications to specific sitesin the human body.

But for now Dr Serrano is driven by theultimate goal of getting that complete pictureof a living organism. “When I give talkseveryone is excited and amazed by the amountof information and what we are doing,” he says.“And the impact will be that we come out witha model that will explain the whole cell in detail.Then we will say for the first time that weunderstand the whole thing.”

Words: Claire O’ConnellOctober 2013

further InformationCentre for Genomic Regulationcrg.es

Having such insights … may also offer routes to

engineer the microbe as a drug-delivery platform to

bring medications to specificsites in the human body.


BAS TEUSINK FROM THE NETHERLANDS PLATFORM FOR SYSTEMS BIOLOGY DISCUSSESTHE REMARKABLE DEVELOPMENTS IN HIS RESEARCH MADE POSSIBLE BY THEAPPLICATION OF SYSTEMS BIOLOGY APPROACHES

We must understand component parts to getto grips with a complicated machine. Once youbuild such a machine yourself, you can tweakand adopt it. Industry understands how to dothis, but has not done so well in deconstructingthe live machinery critical for the fermentationsat the core of so many food andpharmaceutical processes – the microbial cells.

Bas Teusink at the Netherlands Platform forSystems Biology (SB@NL) is mapping out thedesign of microbial cellular networks by askingtwo straightforward but big questions: whatmakes the cell’s biochemical network tick andwhy did evolution choose that design? Hisgroup’s modelling of cells’ metabolic blueprintson a genome scale is yielding some dramaticsuccesses relevant to industrial fermentationprocesses.

His group worked in conjunction with theKluyver Centre for Genomics of IndustrialFermentation, now part of the BE-BasicFoundation, an international public-privatepartnership that develops industrial bio-basedsolutions. This collaboration is putting pep intothe R&D of industries that rely on innovation inindustrial fermentation, optimising what is acritical step in many food, beverage andpharma processes. The aim is to boostperformance and robustness of industrialmicrobes by revealing how the genome andenvironment interact.

Recently Teusink’s group doubled output of acertain toxin, a vaccine component essentialfor a highly contagious but preventable diseasethat kills thousands each year. “We could

deconstruct the metabolic network of theorganism based on its genome,” Teusinkexplains. “In this case it was grown in atraditional production process where ahistorically defined medium was used.” A bigpharma company is involved, but cannot benamed.

Improving the medium would have meant trialand error, but Teusink’s team instead modelledaround 1500 reactions underpinning the cell.They realized an ingredient in the growthmedium impeded production. Teasing out themetabolic networks also showed them thatthe cells would be able to use alternativesubstrates to the ones that inhibitedproduction. They did the heavy lifting in silico,along with experimental test, successfullypredicting an improved formula.

”You can design all sorts of hypotheses thisway about the media. You can ask what are theminimal inputs I need to support growth orwhat are the cheapest materials,” Teusinkexplains. The end result: higher productivity atlower costs. But Teusink’s systems biologyapproach has also yielded a fundamentalbreakthrough, solving a three decade longmutant mystery, recently published in Science(van Heerden et al., 2014).

THE NETHERLANDS PLATFORMFOR SYSTEMS BIOLOGYFOSTERS SYSTEMS BIOLOGYAPPROACHES IN THE RED,GREEN, WHITE AND BLUESECTORS OF THE LIFESCIENCES, CREATINGSYNERGIES BETWEENSYSTEMS BIOLOGY RESEARCHINSTITUTES/GROUPS ANDOTHER STAKEHOLDERS INSYSTEMS AND SYNTHETICBIOLOGY, BIOTECHNOLOGYAND MEDICINE.

Prof. Dr. Bas Teusink developedthe Kluyver Centre SystemsBiology programme; he is FullProfessor in SystemsBioinformatics at IBIVU, VUAmsterdam.

BIOGRAPHY

…it’s only now, because ofour model, that we can

understand thirty years ofresearch…


Researchers had struggled with a particularmutant in yeast for years, but couldn’t figureout this strange phenotype. It can’t grow onglucose, something yeasts normally preferabove all else. Glucose is degraded in ametabolic pathway called glycolysis – Greek forbreaking down sugar. It turns out there are twosolutions to the problem of degrading glucosein these cells; with the mutant form you havea 99.9% chance of not growing on glucose, butthis means that there is still a tinysubpopulation of the mutant that can thrive onit. “This small subpopulation was 1 in 10,000,but we now realize that there are two statesthese yeast can be in,” says Teusink.

When this “bistability” phenomenon wasfurther investigated it turns out 7% of wild typecells by chance do not grown on yeast eitherand normally just die off when fed it.Genetically the two yeast types in both groupsare the same, but chance gives rise toheterogeneity in the system. “This nowexplains all these weird phenotypes in mutantsthat people have generated in this field. So it’sonly now, because of our model, that we canunderstand thirty years of research.”

So far so basic, except that glycolysis is acentral pathway in life and thesesubpopulations are everywhere and areparticularly important during transitions – suchas at the start of a fermentation process whenmicrobes meet a large batch of sugar. “In thesetransitions we often see that only part of thepopulation starts to grow and the other partdies or does nothing. Suppose that youinoculate a million cells in your milk or yourfermentation vat, but only half these cells startdoing something. This will lead to a delay inyour production [a lag phase],” Teusink explains.Once you understand this split in yourpopulation it is possible for you to addsomething to the media as a pre-treatment tocut down on this delay.

All sorts of processes could benefit from agreater understanding of why only some cellsstart to grow. Teusink says his yeast workshows that sometimes the average responseseen in a population of cells is no such thing -it is actually the sum of two completelydifferent behaviours caused by bistability. Suchnoise in life is becoming clearer astechnological advances improve single-cellmeasurements and the theory behind cellularnetwork architecture advances; computers willneed to run even faster to keep up withnetwork models, Teusink predicts.

Teusink, from his base in Amsterdam, believesEurope must try harder when it comes totraining biology students. Today glycolysis istaught as a pathway that goes from A to B, astatic process; students are instructed thatcertain genes are involved, but what does thisreally mean? “The way we should actuallyteach this is to make a model of this pathwayand let students play with it to see how itactually behaves. It’s not so trivial, and stabilityand steady state concepts today are not clearto students,” says Teusink. “Biology iscomplicated and you need the maths.”

Words: Anthony KingMarch 2014

further InformationNetherlands Platform for Systems Biology (SB@NL)biosb.nl/sbnlBE-Basic Foundationwww.be-basic.org

BE-BaSIC faCT fILE

Public-privatepartnership between:27 Industrial partners 7 Research Institutes13 Universities

Since 2011:447 peer reviewed papers8 patents filed8 start ups

Biology is complicatedand you need the maths Lactobacillus bacteria


US PHARMACEUTICAL COMPANY BASES ITS BUSINESS ON A SYSTEMS APPROACH AND ISREAPING THE REWARDS

Merrimack Pharmaceuticals is a NASDAQ-listed biopharma company that has confidentlyplaced its chips on a systems biology approachto cancer drug discovery. The power of asystems approach is to reveal not justindividual components of a system, but howeach part connects.

Peter Sorger, Professor of Systems Biology atHarvard Medical School, helped found thecompany while at MIT in partnership with serialentrepreneur Anthony Sinskey, Professor ofMicrobiology, MIT. Cofounders Ulrik Nielsenand Gavin MacBeath are still with the companyin senior positions.

The very beginning of Merrimack came partlyout of dissatisfaction with the myriadexplanations in the literature of the inductionof apoptosis by anticancer drugs, Sorgerrecalls. They decided it was necessary tounderstand the key physiological pathwaysinvolved in drug response and that that wouldrequire a mix of computational modelling anddynamic modelling.

Merrimack remains rooted in the principles ofgrafting quantitative biology, computationalmodels and engineering to understand thesignalling pathways that are involved indisease in a holistic way and then using theseinsights to identify drug targets, engineer novel

therapeutics and identify biomarkers. Today,Merrimack has a market capitalization of over$900m, has around 270 people on staff and 6drugs in clinical development.

Sorger believes firmly that systems biologyoffers a new path to drug discovery that will befar more efficient. “About 80% of the cost oftoday drugs is in yesterday’s failures, so onetarget for systems biology is to change that: soto reduce the rate at which drugs fail and toincrementally improve the process by linkingthe science back to critical decision making ina company.”

Merrimack’s core values include drilling into thecomplex biology behind cancer. So far this hasyielded the six molecules in clinicaldevelopment. In November, the companyreported news for Phase 2 studies in thetreatment of women with ER/PR2, HER2negative breast cancer with the inhibitor MM-121. A positive signal was shown in asubpopulation of patients that wouldpotentially benefit from targeted therapy. Thefindings support ErbB3 signaling as animportant pathway of resistance for breast,ovarian and lung cancers.

”MM-121 is a monoclonal antibody againstErbB3 but is not as active in HER2overexpressing or amplified tumours.Therefore we designed a second molecule,MM-111, which targets ErbB3 in HER2overexpressing tumours,” says Birgit Schoeberl,Merrimack SVP of Discovery. “Based on ourpreclinical research, we defined five differentbiomarkers that would be predictive of ErbB3activity in tumour samples and designed ourclinical trials to test this hypothesis.” She added

MERRIMACK PHARMACEUTI-CALS IS A BIOPHARMACEUTICALCOMPANY DISCOVERING,DEVELOPING AND PREPARINGTO COMMERCIALIZEINNOVATIVE MEDICINES PAIREDWITH COMPANION DIAGNOSTICSFOR THE TREATMENT OFCANCER. MERRIMACK APPLIES ASYSTEMS BIOLOGY-BASEDAPPROACH TO BIOMEDICALRESEARCH, THROUGHOUT THERESEARCH AND DEVELOPMENTPROCESS.

Peter Sorger PhD is a Professorof Systems Biology at HarvardMedical School and holds a jointappointment in MIT’s Dept. ofBiological Engineering andCenter for Cancer Research.Sorger was co-founder of theMIT systems biology programCSBi, Merrimack Pharmaceuti-cals and Glencoe Software.

Birgit Schoeberl is Senior VP ofResearch with responsibility fordiscovery and clinical stageprojects. She is an internationallyrecognised leader in SystemsBiology. She has been withMerrimack since the verybeginning and has been integralto develop the Systems Biologyplatform.

About 80% of the cost ofdrugs today is in yesterday’sfailures, so the number one

target for systems biology isto change that

BIOGRAPHY


that, with the retrospective analysis of the fivebiomarkers in Merrimack's clinical samplesthey were able to identify a subgroup ofpatients with the same response biomarkersacross NSCLC, ovarian and metastatic breastcancer who appear to benefit from thetreatment with MM-121.

This is the first time we've gone from an in silicopreclinical biomarker hypothesis to theultimate translation into the clinic saysSchoeberl, which is a "big moment forMerrimack and I think for systems biology ingeneral. The predictive biomarkers will helpidentify which patients may benefit from MM-121, which completed six Phase 2 clinical trialsin collaboration with Sanofi.” Merrimackrecently regained worldwide rights to developand commercialise MM-121 in June 2014 fromthe cancer arm of French pharma giant Sanofi.

Merrimack pairs up an experimentalist and amodeller in a “discovery pod” and looks tounderstand the biology before setting off todevelop certain drug candidates. “Early on wemade some proof-of-concept antibodiestargeting ErbB3 and showed that the insightsderived from the model translated into theinhibition of cell proliferation, before starting anantibody campaign and selecting the leadmolecule,” says Schoeberl.

The approach of going under the hood early onto get a good understanding of the biology isessential to Merrimack’s philosophy. It is aboutunderstanding how a drug targeting a specificdisease gene will really work when it gets intoa complex human patient, for example. Theapproach should allow for a betterunderstanding of which patients will respondto which drugs. It could also kill drugs offearlier, says Schoeberl, reducing resource lossthrough expensive late failures.

”Making a drug should ideally be much morelike designing a car or an airplane where it isnot a trial and error process. There is a lot ofdesign and modelling and simulation thathappens even before a car is built,” she says.“We aspire to design and engineer our drugsbased on clearly defined design criteria.” At themoment, the highest number of failures andmost money gets spent before Phase I trials(Tollman et al., 2012). “I believe that SystemsBiology applied to target identification andpreclinical drug development could increase

success rates across the industry,” addsSchoeberl.

”In the future a novel drug that comes out andcosts US$180,000 per year per patient and isunknown if it will work in 50% of the people itis prescribed to, it is not going to be tolerable,”adds Sorger. The systems biology route shouldmean a more quantitative and also morepredictive approach; big pharma is unlikely toturn, however. It is not structured to do so andhas no culture of systems biology. Chances are,agrees Sorger, new systems companies arelikely to be spun out of universities andresearch institutes, as was the case withMerrimack.

Schoeberl herself is a chemical engineer bytraining, having started her career initially inthe oil industry. Her background exemplifiesthe cross-disciplinary nature and quantitativeunderpinnings of a systems approach.Schoeberl then did a PhD in systems biology inher native Germany because she was alwaysfascinated by biotechnology. “The concept ofsystems understanding and systems dynamicsis what you do in chemical engineering. It wasa good background and the biology I basicallylearnt along the way.”

Words: Anthony KingJanuary 2014

further InformationMerrimack Pharmaceuticals www.merrimackpharma.com

This is the first time we've gone from an in silico preclinical

biomarker hypothesis to theultimate translation into

the clinic

MERRIMaCK faCT fILE

2000 Founded by scientists from Harvardand MIT 2011 Announces $77M in private financing 2012 Launch on NASDAQ

270+ Employees $900M Company value

6 Cancer drugs in clinical development

Based on 2014 figures


BLANCA RODRIGUEz ON USING COMPUTER MODELS TO UNDERSTAND THE DIFFERENCESBETWEEN INDIVIDUALS IN THE SUBTLE BUT SOMETIMES CLINICALLY IMPORTANT WAYSTHAT THEIR HEARTS BEHAVE

What makes your heart miss a beat? How ourhearts react to stresses such as disease,exercise and even medicines can vary fromperson to person, and understanding thosedifferences is key for developing more effectivediagnostics and safer therapies.

That’s why Professor Blanca Rodriguez at theUniversity of Oxford is developingsophisticated computer models of howpopulations of heart cells work, and her group’sfindings stand to have a wide impact onrefining simulations of and experiments onliving organs.

Abstract models of the heart are not new -more than 50 years ago Professor Denis Noblecreated the first mathematical model based onthe behaviour of cardiac cells, and the field hasgrown since then, explains ProfessorRodriguez, who is Professor of ComputationalMedicine and a Wellcome Trust SeniorResearch Fellow in Basic Biomedical Sciencesat Oxford.

“Cardiac modelling a very mature area ofcomputational medicine,” she says. “We nowhave multi-scale models of the human heart,so they represent the activity of the heart fromthe sub-cellular to the whole organ level.”

Individual experiments provide snapshots ofparticular aspects of the heart, then the modelcan integrate and reassemble the experimentaldata to build a more complete picture. Thiscomputational model can act as a testbed forsimulations, and the responses can directfurther experiments, which in turn fine-tunethe model. “With the simulations we can

identify key factors that determine ischemicrisk or an adverse response to a drug forexample, then we can test those predictionswith additional experiments,” says ProfessorRodriguez. “So the computation directs thenext round of experiments, and the results ofthese experiments feed into the computationalmodel.”

Such heart simulations offer the advantage ofhigh resolution data both in space and in time,notes Professor Rodriguez: “That means wecan look at any viable property of the tissuethat we want to and we can make calculationsthat are very difficult to do with experiments orclinical methods.”

To improve the simulated heart model, she andher team have brought in an added real-lifecomplication - the differences betweenindividuals in the subtle but sometimesclinically important ways that their heartbehave.

“We are looking at how we can use computermodels to understand inter-subject variabilitybetter,” explains Professor Rodriguez. “Thecurrent cardiac models are based on a genericresponse of a particular cell, but that doesn’t

BLANCA RODRIGUEZ HOLDS AWELLCOME TRUST SENIORRESEARCH FELLOWSHIP ANDIS PROFESSOR OFCOMPUTATIONAL MEDICINE INTHE DEPARTMENT OFCOMPUTER SCIENCE AT THEUNIVERSITY OF OXFORD.

Blanca and her team investigatecauses and modulators ofvariability in the electrophysio-logical response of humanhearts to disease and therapies.Understanding variability iscrucial to ultimately determinewho, when and how patientsmay be at risk, and how toimprove their diagnosis andtreatment. The mechanisms arecomplex, multiscale and non-linear, and Blanca’s teamexploits the power ofcomputational approachescombined with experimentaland clinical research to unravelkey mechanisms of cardiacarrhythmias.

BIOGRAPHY

The computation directs the next round of experi-

ments, and the results of theseexperiments feed into the

computational model.


allow us to investigate why certain peoplereact badly to a medicine or why people die ofa certain disease and not other people. So wehave developed a methodology that allows usto simulate populations of cells rather than asingle cell. This means we can consider a widerange of possible cells, or possible responsesto the same disease or medicine.”

Calibrating populations of cells in the modelwith experimental data means a tightercoupling between the computer model and the‘live’ results, thus building potentially morerealistic simulations with which to test variousconditions.

Such simulations could ultimately help toreduce the levels of animal testing required formedications to assess cardiac side-effects, andDr Oliver Britton - who completed his PhD withProfessor Rodriguez and Dr Alfonso Bueno-Orovio in Oxford - recently won the ‘3Rs Prize’from The National Centre for the ReplacementRefinement and Reduction of Animals inResearch (NC3Rs).

“Bringing in our calibration allows you really totie computational models with a certain typeof experiment,” explains Professor Rodriguez.“And we have created user-friendly software(called Virtual Assay, co-developed with OxfordComputing Consultants) that allows non-experts to run the simulations.”

The researchers are now working with variouscompanies in the life sciences sector to testout the simulations and software, and beingable to generate experimentally-calibratedpopulations in simulations could haveapplications that go even beyond the heart,notes Professor Rodriguez.

“We are looking at exploring pain research inneuroscience and developing models fordiabetes using a similar approach,” she says.

“We want this to have the widest impactpossible and we have been talking to them toshape the research agenda in a way that canbe broadly exploitable.”

Another application of the model is to predictrisk for patients with genetic susceptibilities forhereditary heart conditions such as Long QTsyndrome, which can lead to sudden adultdeath.

“These genetic variations can be characterisedat the ion channel level, so we can plug thatinto our populations of models and determinewhether it is a low or high risk mutation,”explains Professor Rodriguez. “We are alsousing clinical data from partners at The OxfordHeart Hospital - they have in vivo recordingsof hearts that we are using to construct thepopulations and investigate the potential forsimulation there too.”

The Oxford researchers are also scaling up theirpopulations-based model from cells to thewhole heart to examine the impact of ion-channel behaviour on ECG readings, she adds."My group is using the technology in differentways and we are quite keen in exploring howfar it can take us both clinically, in industry andof course in the science we do.”

Words: Claire O’ConnellMay 2015

further InformationDepartment of Computer Science, University of Oxfordwww.cs.ox.ac.ukVirtual Assay: Drug safety and efficacy prediction softwarewww.cs.ox.ac.uk/ccs/tools

We are looking at exploringpain research in neuro-science and developing

models for diabetes using a similar approach


virtual assay

We all respond to medicines in aparticular way. Knowing inadvance how a patient is likelyto react to a drug is importantfor safety, and scientists atOxford are developing user-friendly software to researchpotential effects on populationsof heart cells.

Called Virtual Assay, it generatesvarious models of responsesand calibrates them with datafrom experiments onpopulations of cells. The nowcalibrated model can be testedwith drugs of interest tosimulate a response. Thesoftware has already flexed itscomputational muscles for insilico case studies of specificdrugs and their effects onpopulations of cardiac cells.

THIBAULT HELLEPUTTE FROM DNALYTICS EXPLAINS HOW SYSTEMSBIOLOGY IS HELPING TO DELIVER PERSONALISED MEDICINE PRODUCTS

A Belgian start-up has launched a unique testto determine the type of arthritis a patientsuffers from. Patients may present withinflammatory arthritis, but in a quarter of casesa clinician will not be able to diagnose whichtype it is.

The traditional approach is to wait until thesymptoms become clearer, but this can takeone to three years. During this time the joint ofthe patient can suffer irreversible damage.

Now DNAlytics in Belgium has developedRheumakit, a biomarker-based tool todiagnose patients suffering from undifferenti-ated arthritis. It predicts whether a patientsuffers from osteoarthritis – mechanicaldamage to the joint – or something morecomplex like rheumatoid arthritis, anautoimmune disease. Data analytics andpredictive modeling, along with a systemsbiology mindset, are central to the firm’sapproach.

“The treatments are very different, so this isimportant,” says Thibault Helleputte, CEO andcofounder of DNAlytics. “Our solutioncombines some biological measurements inblood, some clinical observation of the patientand gene expression signature, combined in apredictive way.”

DNAlytics promises “data-driven personalizedmedicine from R&D to market access” in itstagline. It spun out of the UC Louvain’scomputational and engineering departmentand provides consultancy to pharma

companies, especially in situations wheredatasets are so expansive that specificapproaches to modelling of data analysis arerequired. But it also develops personalisedmedicine products.

With Rheumakit, Helleputte realised thattraditional measures like inflammationmarkers in blood were not sufficient fordiagnosis, but could be combined with othermeasures. They started with 50,000candidates of gene expression markers, morethan 10 clinical variables and about the samenumber of biological measurements from thepatients. “We applied feature selectionalgorithms in order to automatically select thefeatures (i.e. the variables) that are mostrelevant to differentiating the differentpathologies,” says Helleputte.

The current diagnostic solution combines threeclinical markers and about 100 geneexpression measures, obtained by looking atRNA expression levels. DNA is fixed, but RNAis a snapshot of metabolism and can varyaccording to disease and medication.

DNALYTICS IS A BELGIANCOMPANY FOUNDED IN 2012 ASA UNIVERSITY OF LOUVAIN SPINOFF THAT BASES ITS ACTIVITIESON A DATA MININGTECHNOLOGY PLATFORM.DNALYTICS COVERS THEDEVELOPMENT OF DATA-DRIVEN PERSONALISEDMEDICINE SOLUTIONS, FROMR&D TO MARKET ACCESS.

Thibault Helleputte is co-founderand CEO of DNAlytics. He holds aM.S. in Computing ScienceEngineering and a PhD inEngineering Sciences from theUniversity of Louvain. Hisresearch work during his PhDcentered on Machine Learningapplied to the design of noveltools for automated predictionbased on genomic technology.

BIOGRAPHY

Our solution combines somebiological measurements in

blood, some clinicalobservation of the patient

and gene expressionsignature, combined in

a predictive way.


The DNAlytics team will take whatever are themost relevant markers for making a predictivediagnosis, whether that is clinical information,imaging data, psychological data or a range ofgenomic, epigenetic or proteomic data. Askedwhat gives the firm an edge, Helleputte saysthey focus not on the performance of theirmodel on already observed data, but rather itspredictive performance for new samples, yetunseen.

“Because when you work with data that havemore variables than observations, so morefeatures than patients say, you are guaranteedto find a perfect model for your data, and thisis really bad news. You will find an infinity ofmodels that look perfect, but these will thenfail to make good predictions on new patients,because they are in fact too specific to the datathat you have already observed.”

Consequently DNAlytics focuses ongeneralisation ability and on multivariatesolutions, meaning that a marker useful incombination with others is preferred, as aremultiple data sources. “We select markers thatwill be more robust, and we developedalgorithms to measure marker (in)stability,”says Helleputte.

Personalised medicine is increasingly enteringoncology practice, with a patient’s tumourgenotyped to see which drugs will work bestagainst it. This is not the case in rheumatology,but DNAlytics is working with rheumatologistsand clinicians to reverse this situation. Thereare around 10 treatments for rheumatoidarthritis, but they are only effective in 60% ofpatients (and each is effective on a differentsubpopulation).

“Right now it is impossible to tell whichtreatment will be beneficial to which patient,so it's trial and error,” says Helleputte. He isworking on genetic profiling and othermeasures to allow the most relevant

treatment to be selected. Anti-TNFs, the mostpopular of which are disease-modifyingantirheumatic drugs (DMARDs), cost Belgiumaround €100 million every year, yet only workon 60% of rheumatoid arthritis patients.“That’s €40 million just wasted,” notesHelleputte. “If you could predict in advancewhich patients will respond to treatment, youcould use the right drug.”

DNAlytics is steeped in a systems biologymindset. It measures the activity of severalmetabolic pathways known to be involved inthe disease or as targets of existingtreatments. “Really understanding all thosepathways and the mechanics behind them, notjust genes or proteins in isolation, but to seehow those elements combine, so from DNA toRNA to proteins to products of degradation, inblood, in serum, in cells, that is key to the futureof our business.”

Helleputte is passionate about the projects heand DNAlytics are wading into. “These are notthe kind of projects you can do in your office, oron your own. You need to meet clinicians, meetregulatory authorities, meet the patients andperform the data analysis. These are reallycomplex projects and that's really stimulatingfor me,” he enthuses.

Words: Anthony King June 2015

further InformationDNAlyticsdnalytics.comRheumaKitwww.rheumakit.com

If you could predict inadvance which patients willrespond to treatment, you

could use the right drug

Rheumakit

How does it work?Clinicians go online andorder a kit. They take abiopsy from the knee of thepatient and put it in the kitwithin vials containing anRNA-preserving solution.The box is shipped to thecompany’s lab in Belgium,which generatetranscriptomic data fromthe sample and uploads theresults onto the webapplication. The cliniciananswers some clinical andbiological questions on thewebsite, and amathematical algorithmkicks into gear and deliversthe diagnosis with a fewseconds. “The processtakes a matter of a fewdays, which is atremendous gain,” saysHelleputte.


PUBLICLY-FUNDED GERMAN FLAGSHIP INITIATIVE IS LEADING THE WAY IN LIVER RESEARCH

Systems biology has now reached a new stageof maturity. No better proof is the existence ofan audacious research project called the VirtualLiver Network (VLN). It provides an excellentexample of how systems biology is nowyielding a level of detail and quantitative datain biology at a scale not previously attained.“We need to do research in biology at the scaleof what astrophysics has done,” explainsAdriano Henney, Programme Director of theVLN.

The aim of the VLN is to design a dynamicmathematical model of the human liver. Thismodel will represent, rather than fully replicate,the liver’s physiology and morphology. Moreimportantly, it will also integrate the wealth ofdata we have acquired post-genome throughmultiple models. Its ultimate goal is torepresent the multiple liver functions, includingdetoxification, the fight against inflammationand the production of biochemicals necessaryfor digestion.

This so-called multi-scale modelling is achallenge. “The ability to model across scalesof time and space is not easily done in biology,”explains Dr Henney. What makes this projectpossible is the data crunching capabilities ofbioinformatics and the power of new computermodelling. This combined approach enablesthe integration of quantitative data from the

sub-cellular levels to the whole organ.Ultimately, better treatments for the manyliver-related diseases are expected to beproduced.

This €50M flagship initiative is supported bythe German Federal Ministry of Research andEducation, BMBF. Research teams that werepreviously in competition are gathered underthe VLN umbrella for five years, until 2015.“This is the first example of an investment insystems biology of this size in a single countrythat focuses on delivering solutions toclinicians, and aiming to do so using simple touse formats,” Adriano Henney points out.

The VLN involves a distributed network ofresearch teams spread over Germany, in 70laboratories. This approach is unique ininternational research in the biosciences. Noteam in the USA, Japan or any other countryhas managed to perform such an intricategeographically distributed researchcollaboration. Nor has any other research effortintegrated the most fundamental biologicalresearch directly through to clinical studies inpatients.

An organ as seemingly anodyne as the liverharbours surprising complexity. Usingmodelling and simulation to tackle thiscomplexity, VLN scientists have been able toshow, according to Dr Henney, “that we canuse it to highlight inaccuracies in our currentknowledge of physiological processes withinthis vital organ”. Specifically, the results of theteam lead by Prof. Rolf Gebhardt, DeputyDirector of the Institute of Biochemistry at the

SINCE ITS BEGINNING IN APRIL2010, THE VIRTUAL LIVERNETWORK HAS ENGAGEDGROUND BREAKING AREAS OFSYSTEMS BIOLOGY IN ACOORDINATED AND FOCUSEDATTEMPT TO SHOW THATMODELLING AND SIMULATIONCAN HELP TACKLE THECHALLENGES OFUNDERSTANDING THEDYNAMICS OF BIOLOGICALCOMPLEXITY.

Dr Adriano Henney isProgramme Director of the VLN.Dr Henney has a PhD inMedicine and many yearsacademic research experience incardiovascular disease inlaboratories in London,Cambridge and Oxford, andworked with AstraZenecaexploring strategicimprovements to the company’sapproaches to pharmaceuticaltarget identification, and thereduction of attrition in earlydevelopment.

€50M flagship initiative issupported by the German

Federal Ministry of Researchand Education

BIOGRAPHY


University of Leipzig, point to inaccuracies inour knowledge of liver steatosis, or fatty liverdisease. The team found that challenging livercells, called hepatocytes, by external fattyacids, results in accumulation of triglycerides infat droplets. However, it only results in minorchanges in the central metabolism of the liver,against all expectations. The team also foundthat the influence of insulin on fatty acidbiosynthesis in liver was previously stronglyoverestimated, while that on the conversion ofcarbohydrates into fatty acids was ratherunderestimated. These findings led to a patentlikely to have a high impact on future therapiesof steatosis and related diseases.

Crucially, the project aims to translate the basicresearch into clinically-relevant applications fordoctors. A team working on a showcase of theinflammatory process in the liver hasdeveloped a user-friendly interface for doctors,available on a tablet. This team is led by Prof.Steven Dooley, a specialist of molecularhepatology at the Mannheim Medical Faculty,and Jens Timmer, an expert in dynamic processmodelling at the University of Freiburg. Theseinflammation models are available toprofessionals without the need for extensivetraining and can be used to help patientsunderstand their illness.

Further concrete results of the VLN projecthave potential applications in medicine. Theyinclude two patents on potential biomarkersfor steatosis, which are pending. These diseaseindicators could ultimately be used as adiagnostic test predicating the onset of fattyliver disease.

The network’s research efforts also draw onexpertise from industrial collaborators,including German pharmaceutical companyBayer Technology Services. Industry partnershave studied some genetic variants connectedto the way individuals metabolise drugs. Thisteam is led by VLN leadership team member,Lars Küpfer. The team’s findings will help

identify patients more likely to benefit fromtreatment. Previously, liver toxicity has beenthe reason for the failure of a significantproportion of novel medicines. Now, systemsbiology is opening new avenues for drugdiscovery.

For now, the team hopes to extend the fundingby another five years, to create the prototypeof a true multi-scale model within a singleorgan and link it to human physiology.

To meet the challenges of 21st Centurymedicine to deliver more effective therapies,we need a deeper understanding of thecomplexity of common disease and thedynamic interplay of genes and environmentthat underpins it. Systems biology offerspotential solutions, examples of which arebeing pioneered in the Virtual Liver Network.

Words: Sabine LouetJanuary 2014

further InformationVirtual Liver Networkvirtual-liver.de

Integrating the mostfundamental biological research

directly through to clinicalstudies in patients

vLn faCT fILE

German government-funded initiative€50M investment over 5 years70 research groups41 Institutions250 Scientists


MICHAEL HUCKA FROM CALIFORNIA INSTITUTE OF TECHNOLOGY ON AN OPENFORMAT FOR CREATING MODELS THAT HAS STIMULATED THE CREATION OF ANINTERNATIONAL COLLABORATIVE COMMUNITY OF SOFTWARE DEVELOPERS

SYSTEMS BIOLOGY MARKUPLANGUAGE (SBML) IS A FREEAND OPEN INTERCHANGEFORMAT FOR COMPUTERMODELS OF BIOLOGICALPROCESSES. SBML IS USEFULFOR MODELS OF METABOLISM,CELL SIGNALLING, AND MORE.IT CONTINUES TO BE EVOLVEDAND EXPANDED BY ANINTERNATIONAL COMMUNITY.

Michael Hucka is a member ofthe professional staff of theDepartment ofComputing and MathematicalSciences, California Institute ofTechnology. His work focuses onthe development of softwarestandards and infrastructure forscientific computing and he hasbeen instrumental in thedevelopment of SBML.

BIOGRAPHY

The emergence of web-based technologieshas catalysed the emergence of systemsbiology, in which dynamic biological structuresand processes can be recast as software codeand computational models. This promises toprovide a powerful new interpretative lens formolecular biologists struggling to cope with theincreasingly large datasets generated by large-scale investments in modern ‘omics’disciplines—such as genomics, transcrip-tomics, proteomics, kinomics andmetabolomics. But if systems biology is tobecome a fully networked discipline—with allof the synergies that that implies—it requiresan underlying information infrastructure akinto that which underpins information andcommunications technology. It needs agreeddata standards and formats for the automatedcreation, publication and exchange of complexbiological information.

The emergence during the past fifteen years ofsystems biology mark-up language (SBML) asa free and open format for creating models, isan important part of this effort. SBML is anapplication of Extensible Mark-up Language(XML), the Worldwide Web Consortium (W3C)standard for formatting documents that nowunderpins data exchange across the publicinternet and private networks. SBML providesa common format for describing the structureand components of biological models.

The role of SBML as the lingua franca ofsystems biology is loosely analogous to that of

hypertext mark-up language (HTML), saysMike Hucka, of the California Institute ofTechnology, a key figure in the creation andongoing development of SBML. “Just as HTMLlets a person or software express somecontent using text formatted in a certainway—with the formatting mark-up normallyhidden from view by software—so too SBMLlets a person or software express certain kindsof data using text formatted in a certain way,”he says. The “certain kinds of data” are usuallybut not necessarily mathematical models ofsome biological phenomena, and the“formatting” is actually descriptions of datafields and relationships between parts of amathematical model, instead of items such assection headings and bold or italic text that youfind in HTML.

The significance of SBML goes beyond itsimmediate role as an information tool. Theemergence of SBML has itself acted as apositive feedback loop in terms of thedevelopment of systems biology. It hasstimulated the creation of an international collaborative community of softwaredevelopers, theoretical biologists and

SBML provides a commonformat for describing the

structure and components of biological models


computational modellers. The reproducibility ofSBML-based models allows for their scrutinyand evaluation by other scientists. Previously,models were typically represented in the formof printed equations, which limited their utility.SBML has enabled the development of curateddatabases of biological models—such as theBioModels Database and JWS Online—whichusers can access and interrogate dynamically.It also underpinned the automated generationof 140,000 biological models from represen-tations of biochemical pathways, in thePath2Models project, which will greatlyaccelerate the development of the entire field.

In setting out the importance of SBML, Huckafrequently invokes a passage written byNicolas Le Novère, of the Babraham Institutein Cambridge, UK: “One of the biggest problemsof ‘Theoretical Biology’ was the failure of twoof Popper's criteria for science: reproducibilityand falsification. I have reviewed papers in thefield for quite a few years now, and there is onecommonality. You can't really evaluate them.You have to completely trust what is written bythe authors. SBML could change that. It couldpermit better evaluation of modelling, and raisethe whole field to a new level of confidence andconsideration by other scientists in life science.”

Ten years on from that observation, it is clearthat SBML, the de facto standard for biologicalmodelling, has delivered on its promise, byproviding a common format that manysoftware systems and users could agree touse. SBML is itself not a static entity. Thespecification is subject to ongoing revision anddevelopment, to take account of changes in theexternal technological environment andchanges driven by developments within thesystems biology field. Over time, people alsofind new needs and desire additions or

changes to existing features in a standard. Allof these activities―corrections, updates andevolutionary changes―need to be done in afair and systematic fashion. SBML Level 3, themost recent version of SBML, has beenstructured in such a way as to enable newextensions to be added with ease. It has amodular structure, with a defined set of corefeatures and additional packages that extendits functionality into specific topic areas.

Notwithstanding its importance, SBML relies,in large part, on voluntary efforts from thedeveloper community to support its ongoingmaintenance and development. Direct fundingis limited to Mike Hucka’s four-strong teamwho support its underlying infrastructure,including the extensive SBML.org website,libSBML, a free, open-source programminglibrary, which enables users to read, write andmanipulate SBML files, and JSBML, a Java-based alternative to libSBML. US NationalInstitutes of Health funding for this work endsin mid-2016. At the very least, follow-onfunding is needed to maintain the ongoingeffort, but a wider level of support for SBML’sbroader development is crucial for the furthermaturation of systems biology.

Words: Cormac Sheridan June 2015

further InformationSBMLsbml.orgCalifornia Institute of Technologywww.caltech.eduEuropean Systems Biology Community community.isbe.eu

The specification is subject toongoing revision and

development, to take accountof changes in the externaltechnological environment

and changes driven bydevelopments within the

systems biology field.

SBML In uSE

Total number of knownSBML-compatiblesoftware packageseach year


DEVELOPMENTS IN STANDARDS-BASED INFORMATION INFRASTRUCTURES AREHELPING BIOLOGISTS TO INTERROGATE ‘BIG DATA’

One of the big challenges for biologicalresearch is its full maturation into a ‘bigscience’ discipline, capable of tackling big,complex questions in a coordinated fashion.The inherent complexity and diversity inbiology makes the maturation harder for thelife sciences than it was for physics, but agrowing adoption of standardisation, data-sharing strategies and attempts to address bigquestions in truly collaborative efforts arespeeding up the process.

The ongoing development of systems biology,which integrates computer-basedmathematical modelling of living systems withexperimental observation, represents animportant strand of this process of maturation.An essential element of this is thedevelopment of robust, standards-basedinformation infrastructures capable ofmanaging large quantities of data andsoftware code in readily accessible formats.JWS Online and BioModels represent twosignificant and complementary modelmanagement initiatives, which are contributingto the ‘digitisation’ of biology by enablingresearchers to explore previously developedmodels of diverse biological processes.

JWS Online, originally developed in 2000 atStellenbosch University (SU; Stellenbosch,South Africa), is now co-developed at theUniversity of Manchester (UM; Manchester,United Kingdom) and the Vrije Universiteit (VU;Amsterdam, Netherlands). It played aprominent role in pioneering the concept ofproviding researchers with online, centralisedaccess to biological models. It includes asimulation environment that enables scientists

to run individual models remotely, eliminatingthe need for painstaking recoding work thatwould be otherwise necessary. “It’s a lot ofwork to code mathematical models from theliterature, and it’s error-prone,” says JackySnoep, Professor of Biochemistry atStellenbosch University. “Every researcher whowanted to use these models would have hadto do the same work.”

JWS Online now contains some 200 curatedmodels, which have been rendered into astandard format using Systems BiologyMarkup Language (SBML), the de factostandard for creating computational models ofbiological processes. The system is alsoemployed by the FEBS Journal, to test modelsthat are submitted for review along withpapers. Reviewers have access to the JWStoolset, via a secure site, and can run themodels, to ensure that the data contained inthe paper can be reproduced by the model.

JWS Online has been incorporated into theSEEK collaboration environment (PubMed:21943917), originally developed for the SysMoproject on the systems biology ofmicroorganisms. The SEEK is a mature dataand model management platform for large-scale systems biology projects. “The data andmodel management structure we set up forthe SysMo project is currently the best systemavailable, and its approach is likely to evolveinto a standard,” says Snoep.

(L-R) Dawie van Niekerk, JohannEicher, Danie Palm and JackySnoep (JWS Online team,University of Stellenbosch)

JWS ONLINE IS A SYSTEMSBIOLOGY TOOL FORSIMULATION OF KINETICMODELS FROM A CURATEDMODEL DATABASE. JACKYSNOEP IS PROFESSOR OFBIOCHEMISTRY ATSTELLENBOSCH UNIVERSITY,SOUTH AFRICA.

the ‘digitisation’ of biology

BIOGRAPHY


BioModels Database, developed at theEuropean Bioinformatics Institute (EBI;Hinxton, UK) since 2005, was created inresponse to the needs of the community for amodel repository. It reflects the growingnumber of models published in the literatureand provides them in a computationallyreusable form. These models originate from aplethora of domains representing work thatspans decades of refinement. Notableexamples include:• Synthetic biology (BIOMD0000000012)• Neurobiology (BIOMD0000000020)• Oncology (BIOMD0000000234)• Virology (BIOMD0000000463)• Immunology (BIOMD0000000243)• PK/PD – Systems Pharmacology

(BIOMD0000000490)

BioModels Database is now by far the field’slargest repository of biological models, havingamassed more than 1,000 manually curatedbiological models. Each of these models aredescribed in peer-reviewed publications,manually curated to verify that the model inthe database is capable of reproducing thepublished results, and is extensively annotatedto specify the biological entities that arerepresented within the model. Additionalannotations are also provided that link themodel itself to further information such asmathematical concepts, ontological terms(including those that reference biologicalprocesses), and to other models (allowinghierarchical analysis on model lineages). Over300 journals recommend deposition of modelsdirectly to the database in their submissionguidance notes to authors.

With the ever-growing means by which 'bigdata' is generated, there is an ever-evolvingneed to deal with it. The BioModels team hasrecently introduced a means to automaticallymanage models from large data sets; Besidesthe 1,000+ curated models, BioModels alsonow contains an additional 140,000 modelswhich were generated automatically from rep-resentations of biochemical pathways takenfrom multiple sources. Collectively, these

models cover domains such as metabolism,signal transduction, electrophysiology,population and ecosystem dynamics, pharma-cokinetics and pharmacodynamics, andmechanisms of disease. “We are fulfilling theclassical library function in this domain—wehave the record of the developed models,” saysHenning Hermjakob, head of the EBI’sproteomics services team.

BioModels is not just a passive repository—itis a true database, which can be interrogateddynamically. Models can be readilydownloaded or can be run remotely usingseveral different tools, including the JWS Onlinesimulation environment. A ‘Model of theMonth’ feature enables new users to learnabout important individual models in a largelyjargon-free way; BioModels provides a varietyof teaching materials and resources, and canbe regarded, says Hermjakob, as a portal to theworld of modelling.

Modelling biological systems continues toevolve from being an early-stage endeavour.The field has taken major steps in recent years,culminating in the publication of the firstwhole-cell computational model, whichpredicts a cell’s phenotype (or visible charac-teristics) from its genotype (or genetic make-up) (Karr et al., 2012). JWS Online andBioModels are both vital components of theinformation infrastructure supporting theseefforts.

Words: Cormac SheridanJanuary 2014

further InformationJWS Online jjj.biochem.sun.ac.za BioModels Database www.ebi.ac.uk/biomodelsThe SEEK www.seek4science.org SysMo www.sysmo.net Path2Models code.google.com/p/path2models

a true database, whichcan be interrogated

dynamically

CURRENT DEVELOPMENTSIN CARDIAC CELLMODELLING

BioModels Database serves as areliable repository of computationalmodels of biological processes, andhosts models described in peer-reviewed scientific literature.Recently it has also begun toincorporate models that can beautomatically generated from 'bigdata' pathway resources. HenningHermjakob is team leader ofProteomics Services at the EuropeanBioinformatics Institute, based inHinxton, Cambridge.

a Growing database

2005 2013

Models 20 1000+

Species 300 400,000+

Cross- References 1000 1,000,000+


UK ONLINE COURSE IS CREATING NEW GENERATION OF SYSTEMS BIOLOGISTS

A UK initiative is delivering a thriving andexpanding online course in systems biology,Systems training in Maths, Informatics andComputational Biology (SysMIC). The course,which is now looking to spread beyond the UK,serves up introductory and advanced trainingin maths and computing, but always withbiological examples.

SysMIC sprang from a desire by a UK researchcouncil to ensure its workforce had themathematical and computational horsepowerto engage with systems biology and the inter-disciplinary science agenda. Funded by theBiotechnology and Biological SciencesResearch Council in the UK and run by aconsortium of University College London,Birbeck College, the University of Edinburghand Open University, SysMIC has immersedparticipants in programming MATLAB to modeland simulate biological systems and and usingR statistical software. The core team at UCLcomprises Geraint Thomas, Gerold Baier, webtechnologist Philip Lewis and administratorHannah Lawrence, and the course has alreadyserved up skills and confidence to over onethousand biologists.

Twelve of the 14 University Doctoral TrainingPartnerships funded by the UK’s Biotechnologyand Biological Science Research Council haveadopted the course as core training for theirPhD students, but it caters too for establishedresearchers wishing to brush up their skills. “Itis for anyone interested in biosciences, frommolecules to ecosystems, and for all levels ofseniority,” explains Geraint Thomas, the cellularbiologist at University College London, UK, wholeads SysMIC.

They will emerge with skills suited to modellingbiological systems, be it ecological systems orthe growth of organisms or cell signallingpathways. Plus, they will no longer be baffledby other people’s simulations of the biologicalworld.

“The immediate aim is that they can read apaper, recognise the assumptions made, lookat the code and check it if they want,” saysThomas. There are three modules, each lastsix months and requiring five hours work perweek – progressing from basic skills toadvanced topics and then project work.

Course organisers say undergrad and postgradstudents too often see their maths skillsatrophy as biology courses pack in coresubjects and squeeze maths out. SysMIC willinstil linear algebra, dynamical systems, anddifferential equations, but turn maths teachingon its head. Traditionally teaching starts withmaths and seeks applications.

“We start with a biological example and askwhat kind of mathematics is needed,” saysGerold Baier at UCL. Computationally theprogramming language of MATLAB and Rstatistical package are taught, giving the basicsto set up code, analyse data and write a scriptto run a model. Real papers are chosen, butnothing too advanced for beginners.

SYSMIC IS A COMPREHENSIVEONLINE COURSE IN SYSTEMSBIOLOGY AIMED ATRESEARCHERS IN THEBIOLOGICAL SCIENCES. THECOURSE PROVIDESINTRODUCTORY ANDADVANCED TRAINING INMATHS AND COMPUTINGBASED AROUND BIOLOGICALEXAMPLES.

Geraint Thomas is the lead onthe SysMIC project and is basedin the Department of Cell andDevelopmental Biology atUniversity College London. He is a core member of theUCL/Birckbeck Institute ofStructural Molecular Biologyand the admissions tutor andPhD liaison for theUnderstanding BiologicalComplexity PhD programme atCoMPLEX.

Gerold Baier leads thedevelopment of the SysMICcourse and is based in theDepartment of Cell andDevelopmental Biology atUniversity College London. Witha background in biochemistryand nonlinear dynamics, hisresearch work is on developingcomputational models ofepileptic seizure dynamics.

BIOGRAPHY

SysMIC is for anyoneinterested in biosciences, frommolecules to ecosystems, and

for all levels of seniority


Trainees see gains in being able tocommunicate with mathematicians,statisticians and computer scientists. “It is thecommunication skills that people value most.They learn how to think in a structured,quantitative way, and are able to talk tospecialists in a way that allows them gainmuch more profound advice,” Baier explains.

The course is woven to fit time-poor people,engaged full time in biological research. Thereis strong demand from pharma. “The pharmaindustry have employed people with abioscience or pharmacological degree, butoften little mathematical or programmingtraining, yet the nature of data today meansthat you must use quantitative andcomputational means to deal with themproperly,” says Baier.

Bespoke parts for bioscience industries arebeing created, which focus on experimentaldesign, statistical analysis and how to optimisethose in drug discovery programme. The corematerial is akin to a solid trunk of taughtmodules, but with branches now beginning togrow out to cater for individuals or particulargroups.

That the future of biology is going to be moremathematical is hardly a revelation. This wasclear 15 years ago, says Thomas, “but it hastaken a while to turn around the training supertanker.” Thomas set out as a biochemist,tacked to a more multidisciplinary line, beforedevoting six years to a maths degree at theOpen University, UK.

“I enjoyed it straight away. I got a buzz out ofsolving things. ” says Thomas. “But at everystage of my degree I was thinking, I can applythis to my research, or my colleague could usethis mathematical approach.” Those taking thecourse often say they spend so long dealingwith complexity that it is satisfying to haveclear answers to problems.

SysMIC adds new papers, examples anddatasets continuously, along with multimediaresources. There are online tutors and anexpanding FAQs pile. Course quizzes serve toreassure people that they are making progress,while supervisors, line managers or a trainingteam can determine whether sufficient highstandard is being achieved. Course sponsorstypically expect 70% of course questions to becompleted by students, with the remainderdevoted to a mini-project, but that can beadjusted.

The course never sits still. It’s expanding totake on a parallel version with the Pythonprogramming language. As new languagesestablish themselves, organisers will build newversions of the course, which will stand as aperpetual resource. “If you do it in MATLAB and3 years later you realise you need some Pythontraining, then you can go back and see familiarmaterial and take on all the examples in acompletely different language,” Thomas says. Another major objective he has is to movebeyond the UK and embrace Europeanscientists. “Now that things are working out,we want to expand into Europe.”

Anja Korencic at the University of Ljubljanabegan the course to assist her with modellingin her research project on circadian clocks. “Ihad some MATLAB, but I was looking for asystematic introduction to modelling and to beable to communicate with modellers.” She isimpressed by how the course begins at a basiclevel, taking you through step by step, and howit is really designed for biologists. “I thought Imight skip over some of the early sessions, buteven the first and second sessions had somereally nice tricks or details that proved reallyuseful for me.”


further InformationSysMICwww.sysmic.ac.uk

Now that things areworking out, we want to

expand into Europe

The SysMIC course comprises ofthree modules, each takingapproximately 6 months tocomplete:

Modules 1 and 2 consist of aseries of units based aroundbiological examples which aresupported with mathematicalbackground reading.The biological examples showshow the maths techniques canbe used to model biologicalsystems, with code examples ofcomputer programming.Students are taught usinghands-on code examples inMATLAB (used for mathematicalanalysis and modelling) and theR package (used for dataanalysis).

Module 3 consists of support forstudents undertaking anextended project to apply inter-disciplinary skills to their ownarea of interest.


PEDRO MENDES FROM THE UNIVERSITY OF MANCHESTER EXPLAINS HOW BIOLOGISTSARE BEING GIVEN A HELPING HAND TO INTRODUCE MODELLING INTO THEIR RESEARCH

The best front-of-house greetings are friendlyand do not require you to know what’s goingon behind the scenes. This trend is seen intechnology with intuitive digital user interfacesdeveloped for simplicity and ease of use, hidingthe heavy duty lifting. But there is ananalogous option for biologists.

COPASI is an open source software packagethat offers biologists a guiding hand inmodelling and simulation. This is a welcomeservice given how modelling and simulation isincreasingly needed to aid the understandingof cellular behavior and to facilitate aquantitative reading of experiments.

“The software was made to target thosebiologists who want to do modelling, but don’tnecessarily have all the mathematicalbackground. The software tries to hide someof the mathematics behind the user interface,so the user doesn’t need to know all thealgorithms being used,” says Pedro Mendes,Professor of Computational Systems Biologyat the University of Manchester, UK, and aleader in its development.

“It allows researchers to create models ofbiochemical networks and then using differentalgorithms to simulate them and analyse theresults.”

Cells are composed of many organelles; so thissoftware allows the reactions to be distributedacross several compartments. It is used insystems biology to develop reaction kineticmodels for biochemical networks, to simulatetheir behavior and to analyse their properties.Models can be based on ordinary differentialequations or stochastic kinetics.

The software began its journey in 2000 ascollaborations between Mendes and UrsulaKummer, biological modeller at the Universityof Heidelberg, Germany. The first versionlaunched four year later in 2004.

Under the hood it had two major types ofsimulations. One for simulating biochemicalnetworks with differential equations, which isthe most traditional approach and probably themost widely used. “Essentially users describea network and the software builds differentialequations for them, based on the network andsome mathematical details they may need toadd,” Mendes explains.

The other type – stochastic simulations –considers each molecule as a single entity,takes on more of the physical details of thewhole network and offers more accurate, moremechanistic simulations. But COPASI makes itstraightforward for researchers to switchbetween the two. “You can tell the software todo it this way or that, and it tries to doeverything automatically,” says Mendes.

COPASI IS A SOFTWAREAPPLICATION FOR SIMULATIONAND ANALYSIS OFBIOCHEMICAL NETWORKS ANDTHEIR DYNAMICS. COPASI IS ASTAND-ALONE PROGRAMTHAT SUPPORTS MODELS INTHE SYSTEMS BIOLOGYMARKUP LANGUAGE (SBML)STANDARD AND CANSIMULATE THEIR BEHAVIORUSING ORDINARYDIFFERENTIAL EQUATIONS(ODES) OR GILLESPIE'SSTOCHASTIC SIMULATIONALGORITHM.

Pedro Mendes is Professor ofComputational Systems Biologyat the University of Manchesterand Professor in Residence atthe University of ConnecticutHealth Center. His research is inthe area of computationalsystems biology, which aims tobetter understand biologicalsystems through the use ofcomputer models.

BIOGRAPHY

COPASI allowsresearchers to create

models of biochemicalnetworks and then using

different algorithms tosimulate them andanalyse the results


COPASI is not standing still. Differentalgorithms are added all the time, withparameter estimation now an option: thisessentially links experimental data with themodel, building a bridge between the modeland what is observed.

Being open source, COPASI’s success can bedifficult to precisely quantify. But with 10,000downloads last year and a registeredcommunity of 2,000 users, it is obviously apopular computational tool.

Right now, the Mendes and Kummer labs areresponding to user demand by introducingdelay differential equations, which are types ofmodels that have explicit delays built in; it isimportant in fields like circadian biology but hasuses in other areas too.

“If a pathogen invades a person, the immunesystem takes a while to respond. Sometimesyou don’t need to account for that delay,” saysMendes. “But sometimes researchers want tomake a higher level model where they add aspecific delay in the model. If the systemresponds five hours later, this must berepresented in a specific algorithm.”

COPASI is able to import and export in SystemsBiology Markup Language (SBML), which is afree file format useful for exchanging modelsof metabolism and cell signaling and more.

What other options are open to researchers?People can write their own specific software inlanguages like C or python says Mendes, whichis how he started out when doing his PhD. Thisled him to develop GEPASI in the early 1990s,the precursor of COPASI. “The number ofpeople writing their own programmes issmaller now,” he says. “The majority of peoplewho don’t use COPASI use MATLAB, acommercial package designed originally forengineers.”

MATLAB requires researchers to learn someMATLAB programming language. “Learningour software should be easy and the languageused is often specific to biochemistry,” Mendesexplains.

He compares it to the difference betweenWindows and DOS – where you had to type inand remember commands. For windows, youuse macros and icons and don’t need toremember everything. That is how COPASIworks. It essentially has menus and dialogueboxes and icons and people click on thesethings and build the model up. Still, SBMLmeans researchers can test models out oneither or both packages.

Putting his perfectionist hat on, Mendes saysthey are striving to improve the software andlearning tools for users.

It is open source, so others can contribute. “Wehave an API (an application programminginterface) which is essentially a way of allowingother people to write programmes and usepart of COPASI in their programmes,” saysMendes.

They have posted instructive clips on YouTube,introducing COPASI and giving tutorials onwhat you can do with it. The Mendes andKummer labs often give workshops atconferences with the lessons learnt fromwatching users helping them to continuallyimprove this vital software package.


further InformationCOPASIwww.copasi.org

Learning our softwareshould be easy

COPaSI faCT fILE


Copasi is aninternationalcollaborationbetween:

10,000 downloadsin 2014

Community of2,000 users

KATY WOLSTENCROFT FROM THE UNIVERSITY OF LEIDEN DISCUSSES HOW THE WEB-BASED SEEK PLATFORM IS ENABLING SCIENTISTS GREATER ACCESS TO AND MOREINTELLIGENT USE OF THE VAST REPOSITORIES OF BIOLOGICAL DATA BEING AMASSED

The increasing data intensity of biologicalresearch, which is closely linked to theincreasing complexity of scientificcollaboration, has created an urgent need fornew tools to allow researchers to navigate theever-expanding information universe. Systemsbiology, the emerging discipline that seeks tomap precisely all of the dynamic processeswithin living cells and organisms, has createdvery particular data managementrequirements. At its core is a tight couplingbetween experimental data and datamodelling, as predictions and hypothesesbased on computer models are testedexperimentally, which can lead to furtherrefinements in the model or to revisions incertain parameters. The scale and complexityof the data that are generated requirestandards of data stewardship that representsignificant challenges to biologists and datamanagement specialists alike.

The SEEK platform is a commons interfacewhich has grown out of a large-scale Europeanproject on the systems biology ofmicroorganisms (SysMO). It represents anambitious attempt to capture the complexitiesof systems biology research within a web-based data management and collaboration

environment, in order to maximise the use andreuse of the data that are generated. Theplatform extends into the systems biologydomain concepts and standards developedunder the semantic web initiative of the WorldWide Web Consortium (W3C), an ongoing effortto present disparate forms of information inmachine-readable formats, to enable moresophisticated forms of data searching andanalysis across distributed systems.

SEEK was developed by researchers based atthe University of Manchester (UK), theHeidelberg Institute for Theoretical Studies(Germany) and the University of Stellenbosch(South Africa) in response to a requirement onthe part of SysMO’s funders that its grantees,who are distributed across more than 100institutions located in six countries, share dataand data models. Before SEEK there was noobvious way to do this in any kind ofcomprehensive or controlled fashion.Researchers shared data by exchanging verybasic forms of documentation, such asspreadsheets, by setting up project-specificwikis or by using generic web-based or cloud-based collaboration environments, which arenot adapted to the specific methodologies orinformation architectures of systems biology.

The SEEK system acts both as a repository,which allows users to publish and share dataand models, and as a registry, which provideslinks to relevant data sources and modelshosted elsewhere. Its main componentsinclude an assets catalogue, which holds datafiles, protocols, workflows, models and

THE SEEK PLATFORM IS A WEB-BASED RESOURCE FORSHARING HETEROGENEOUSSCIENTIFIC RESEARCHDATASETS, MODELS ORSIMULATIONS, PROCESSES ANDRESEARCH OUTCOMES. ITPRESERVES ASSOCIATIONSBETWEEN THEM, ALONG WITHINFORMATION ABOUT THEPEOPLE AND ORGANISATIONSINVOLVED.

Dr Katy Wolstencroft is anAssistant Professor at theLeiden Institute of AdvancedComputer Science (LIACS),teaching courses inbioinformatics and computerscience. Dr Wolstencroftpreviously was a ResearchFellow in the School ofComputer Science, University ofManchester working onscientific workflows with theTaverna workbench, andSystems Biology data andmodel management with theSEEK platform.

BIOGRAPHY

an ambitious attempt to capture the complexities of

systems biology research … tomaximise the use and reuse of

the data that are generated


publications; a ‘yellow pages’ feature, whichcontains information on SysMO participantsand their host institutions; and an accesscontrol feature, which enables user to controlthird party access to their data.

One of the main challenges inherent in itsdesign was to create a system that wassufficiently powerful and robust to be useful,while not placing an excessive burden on itsusers. Biological information is inherentlyheterogeneous and complex. Systems biologygenerates multiple types of data, includingvarious species of ‘omics data (genomics, tran-scriptomics, proteomics, metabolomics, etc.),imaging data and enzyme kinetics data. Toenable all of this to be managed coherently ina web environment, data and accompanyingmodels and experimental protocols need to be‘annotated’ or described in a precisely definedmanner, and the relationships between thevarious elements must also be specified.

The SEEK system can generate this‘metadata’—or data about data—on the fly, asusers deposit data held in commonly used fileformats, such as spreadsheets, usingpredefined templates. This eliminates whatwould otherwise represent a significantoverhead for users. “There are not that manyincentives for people to spend time curatingand annotating their data and their models,”says Katy Wolstencroft , a member of the SEEKdevelopment team at Manchester (now at theUniversity of Leiden, in the Netherlands.).

The system also draws on the ISA framework(Investigation, Studies, Assays), an emergingsoftware standard for managing biosciencesdata.

SEEK can be readily adapted for any systemsbiology project. Its user base has, in fact, grownto more than a dozen other implementationssince it became available via an open sourcelicence in 2010. These include the EuropeanVirtual Institute of Malaria Research(EVIMalaR), a Network of Excellence

established under the European Commission’s7th Framework Programme (FP7), which hasdeployed SEEK to develop a comprehensivepicture of research activity within the network. The Virtual Liver Network, which comprises 70research groups distributed across Germany,has implemented SEEK to enable its membersto find and share data, models and processesthat relate to liver function—at multiple levelsof organisation, from the individual cell up tothe complete organism. Other users include:Unicellsys, another FP7 project, which isdeveloping a quantitative understanding of thecontrol of and coordination of cell growth inresponse to internal and external triggers;JenAge, a German research initiative on thesystems biology of ageing; and ROSage,another German project, which is exploring therole of reactive oxygen species in the agingprocess.

SEEK is part of a wider ecosystem ofstandards-compliant, open-source systemsthat will, ultimately, facilitate greater access toand more intelligent use of the vastrepositories of biological data that are beingamassed globally.

Words: Cormac SheridanDecember 2013

further InformationThe SEEK platform www.seek4science.orgISA framework (Investigation, Studies, Assays) www.isacommons.orgSysMO www.sysmo.eu

The SEEK … eliminates whatwould otherwise represent asignificant overhead for users

SEEK In uSE

German government-fundedinitiative€50M investment over 5 years70 research groups41 Institutions250 Scientists


acknowledgements

This publication was produced by Systems Biology Ireland, University College Dublin, as part ofthe Infrastructure for Systems Biology Europe (ISBE) programme, supported by an EU FP7Infrastructure award (Grant agreement no: 312455).

We would like to thank the interviewees for generously giving up their time to talk about theirwork, as well as their support teams for providing additional information.

Editor: Will Fitzmaurice, Systems Biology Ireland Writers: Anthony King, Sabine Louet, Claire O’Connell, Cormac Sheridan Design: Resonate Design

Image credits

Profile photographs courtesy of the researchers and their institutions unless otherwise stated.

Page 4 Denis Noble: SBMC 2010 © Britt SchillingPage 4 ap_i/ShutterstockPage 4 CLIPAREA/ShutterstockPage 14 YanLev/ShutterstockPage 20 Nerthuz/iStockphotoPage 25 Stuart Dunbar at outreach event ©Layton ThompsonPage 26 Happetr/ShutterstockPage 28 bymandesigns/ShutterstockPage 29 Thibault Helleputte © Laetizia BazzoniPage 30 Rheumakit © DNAlyticsPage 32 zebrafish image courtesy of Melinda HalaszPage 32 University College Dublin researchers © UCD

Contact

For further information on Infrastructure for Systems Biology Europe, visit www.isbe.eu.

For further information on this publication, please contact:Will FitzmauriceSystems Biology IrelandUniversity College [email protected]

Copyright © 2014 UCD. All rights reserved

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