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The PL-Grid Virtual Laboratory in the Life Sciences Domain

Maciej Malawski, Eryk Ciepiela, Tomasz Gubała, Piotr Nowakowski, Daniel Harężlak, Marek Kasztelnik, Joanna Kocot, Tomasz Bartyński,

Marian BubakInstitute of Computer Science AGH

ACC Cyfronet AGH

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OutlineMotivation – complex scientific applications

on modern computing infrastructuresIn-silico experiments and Virtual LaboratoryGridSpace2 as a solution

ArchitectureWorking with GridSpace

Examples of applicationsComputational chemistryBioinformatics

Conclusions

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MotivationComplex scientific applications on

modern computing infrastructures Clusters, Grids, Clouds

Diverse software packages Applications (Gaussian, NAMD,…) Web Services Scripts: Perl, Python, Ruby

Different users Chemists, biologists Programmers End users

Various data types Files, databases, URLs

Exploratory programming Unstructured, dynamic, prototyping

Collaboration Teams, communities

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Experiment Experiment (in-silico)- a process that combines

together data with a set of activities (programs, services) that act on that data in order to produce experiment results Experiment plan – a specific type of software Experiment run – a specific execution of the experiment

Complex workflow going beyond manual simple and repeatable execution of installed programs

Combines steps realized on a range of software environments, platforms, tools, languages etc.

Developed, shared and reused collaboratively amongst ad-hoc researching teams

Composed of collaboratively owned libraries and services used (called gems) and experiment parts (called snippets)

Virtual Laboratory – environment for development, execution and sharing of experiments

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Working with GridSpace2Easy access using Web

browserExperiment

Workbench Constructing experiment

plans from code snippets Interactively run

experimentsExperiment Execution

Environment Multiple interpreters Access to libraries,

programs and services (gems)

Access to computing infrastructure Cluster, grid, cloud

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Experiment Workbench

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Binding sites in proteins Comparison of Services for Predicting

Ligand Binding Sites Multiple services available on the Web Conversions between data formats Visualization scripts (Jmol, Gnuplot) Single access based on experiments

developed in Virtual Laboratory Calculation of hydrophobicity profiles

Multiple scales, parameters, input data Computed using PL-Grid resources –

easy access to Zeus cluster at Cyfronet Management of experiment results:

~ 1 Million output files Using semantic integration framework

for metadata management

Collaboration with Departament of Bioinformatics and Telemedicine, Jagiellonian University, Prof. Irena Roterman-Konieczna, Katarzyna Prymula

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Analysis of water solutions of aminoacids Involving multiple steps realized with many

tools, langauges and libraries used for Packmol – molecular dynamics simulations

of packing molecules in a defined regions of space

Jmol – visualization of solution Gaussian – computing a spectrum of the

solution Python/CCLIB – extracting spectrum info jqPlot – displaying plot

Collaboration with computational chemists of ACC Cyfronet AGH and Departament of Chemistry, Jagiellonian University, Dr. Mariusz Sterzel, Klemens Noga

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ConclusionsComplex scientific applications need

dedicated tools and approaches.In-silico experiments are supported by Virtual

Laboratory powered by GridSpace2 technology.

Applications:BioinformaticsComputational chemistryMore are welcome!

Virtual laboratory is open for PL-Grid users.

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Referenceshttp://wl.plgrid.pl

– open the Virtual Labortory in your browserhttp://gs2.cyfronet.pl

– learn more about GridSpaace2 technologyhttp://virolab.cyfronet.pl

– see our earlier achievementshttp://www.plgrid.pl

– become a user of PL-Grid