WHAT THE IOT SHOULD LEARN FROM THE LIFE SCIENCES

• Computational biologist• Research group leader• Lecturer in genome biology• Advisor at• 2015 Fellow of the

Who is@BorisAdryan

DNA = storage of a blueprint

RNA = ‘active copy’ of DNA

protein = the building blocks of cells and tissues

LIFE AS WE KNOW IT

transcription

translation

Gregor Johann Mendel,exhibited in the Library at the NIMR

• Reading DNA information

• Determining “the sequence of a gene” was a PhD in the early 1980s

• Data processing was mainly transcribing the observation into a research paper

BIOLOGY THEN AND NOWSEQUENCE INFORMATION

Sanger sequencing ca. 1980

http://www.eplantscience.com

181,563,676,918 bases base pairs on 15th October 2014(from 165,722,980,375 bases on 24th August 2014)

• We can sequence a human genome in half a day

• Sequence databases grow faster than storage capacity

• Data processing is the key step in scientific understanding

BIOLOGY THEN AND NOWSEQUENCE INFORMATION

BIOLOGY THEN AND NOWGENE ACTIVITY INFORMATION

• When are genes needed?

• Classical molecular biology workflow, taking days…

• Data is semi-quantitative; testing one gene at the time

Northern blot for d-vhlca. May 1999

• High-throughput gene expression profiling since mid-1990s

• Quantitative information for every gene in an organism

• Key challenge is the presentation and interpretation of the data

BIOLOGY THEN AND NOWGENE ACTIVITY INFORMATION

26 ATP

• Signal transduction and metabolic pathways

• Characterisation of proteins and substrates that mediate chemical reactions

• Nobel prize material

BIOLOGY THEN AND NOWBIOCHEMISTRY

• We know about 250k metabolites

• 100k protein structures

• on the order of 10k different chemical reactions

BIOLOGY THEN AND NOWBIOCHEMISTRY

‣ Everything is connected‣ Big, noisy, often

unstructured data

‣We are learning how biological entities depend on each other

‣ Everything is connected‣ Big, noisy, often

unstructured data

www.thingslearn.comAnalytics, context integration, machine learning and predictive modelling for the IoT.

THERE’S NO ANALYTICAL FLEXIBILITY IN M2M/IOT

Matt Hatton, Machina Research The BLN IoT ‘14

Internet replaces wire

It’s all about the connectedness

M2M

consumer

IoT

LIFE SCIENCE STRATEGIES DON’T WORK IN THE IOT- There are no commonly accepted

- ‘catalogue’ of things,- ‘ontology’ of things,- ‘data format’ of things,- ‘meta data’ for things.

- Most businesses are driven by revenue, not long-term strategic vision

- Service providers have no need to publish

- Data can be highly personal (cheap excuse)

unless they’re

WE FIXED OUR KNOWLEDGE REPRESENTATION PROBLEM

FORMALISING KNOWLEDGE

FORMALISING KNOWLEDGE WITH GENE ONTOLOGY

CURRENT GOVERNMENT INVESTMENTS INTO GENE ONTOLOGY

NIH alone spent $44,616,906 on the ontology structure since 2001(no data for UK/EU spendings)

~100 full-time salaries for experts with domain-specific knowledge

~40,000 terms

Oct. 1995

TOWARDS MIAMI AND DATA REPOSITORIES

cf. IoTNov. 1993

META DATA, SHARING AND DATA REPOSITORIES

founded in Nov. 1999

But this is a complex and ambitious project, and is one of the biggest challenges that bioinformatics has yet faced. Major difficulties stem from the detail required to describe the conditions of an experiment, and the relative and imprecise nature of measurements of expression levels. The potentially huge volume of data only adds to these difficulties.

NatureFeb. 2000

“

“

Nov. 2000 Oct. 2002

Wide adoption as requirement for publication in scientific journals

META DATA, SHARING AND DATA REPOSITORIES

cf. IoT 2014

since 2003

Semantic Sensor Network Ontologyhttp://en.wikipedia.org/wiki/Silo

story

measurements + meta data

open, public repositories

human curators

ontology terms

community

PUBLISH OR PERISH

ok?

journal

informal exchange - no credit!

funders

assessment

The majority of this infrastructure is paid for by governments and charities

industry!

measurements + meta data

storage & provenance

human curators

ontology terms

user

PUBLISH OR YOU’RE NOT DOING IOT

ok?

Maybe the majority of this infrastructure should be paid for by governments?

companycloud

device registration

“ “

privileges dataadded value

WHAT THE IOT SHOULD LEARN FROM THE LIFE SCIENCES

• Given the predicted importance and impact of the IoT, we can and should not leave the development of infrastructure to commercial stakeholders alone.

• We need a lot more incentives to participate and targeted investment from the government (“the funders”) into reliable infrastructure.

• It took the computational life sciences less than 4 years(!) to grow from a grass roots movement to having industry-scale, expandable infrastructure.

• Shared vision, dogmatic implementation, effective lobbying.

@BorisAdryan is interested to hear about IoT job opportunities.