Eclipse Meets Systems Biology


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Presentation given at EclipseCon2010 about the uses of Eclipse in Systems Biology software.

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  • Different levels of organization – -emergent properties – beating of heart – how does arise from molecular interactions in heart cells? what level is appropriate for modelling e.g., heart disease? Ideally information and data needed at all levels to generate a complete model – but does simulating the heart does require simulating all chemical reactions that go on.Systems biology aims to understand biological function using info from all levels- aims to achieve this through building quantitative models that can be simulated => predictions can be made
  • Cell – basic building block of life- incredibly complex. - yet secrets of most diseases lie within the walls - biology up to early 2000s essentially reductionist - identifying toolkit of parts and functions in isolation
  • How to fix a broken car?Biologists would take several approaches: E.g., compare broken & non-broken carsBiochemist – take 100 cars, put them in a blender – identify chemical constituentsGeneticist – remove one element (gene) at a time and observe effect on car function (phenotype)(based on Lezebnik 2002)Microscopist – cut car into thin sections, get fine level structural detail.Reductionist approach – looking at components in isolation - need to look at interconnections between components - complex interactions (e.g., antenna length, tuning and volume)
  • Left diagram is biologists description of a car - qualitative, missing information, and ambiguousEngineering diagram: unambiguous, quantitative, predictive. Complexities reduced – ‘correct level’ for fixing a car part. ‘Black boxes’ that encapsulate detail
  • – knowledge of component parts - create rate equations that explain how activities change over time - use experimental data to parameterize the model - run simulations of model, simulate effects of mutations, drugs etc - generate hypotheses to test in the lab.
  • Illustrative example of previous slide{{S}ystems biology reveals new strategies for personalizing cancer medicine and confirms the role of {P}{T}{E}{N} in resistance to trastuzumab}
  • Wide spectrum of software usageFrom mathematical to qualitativeDifferent user skills Most users differentResearch based projectsMany more biologists than modellers – potentially larger use-base needing to access more technical functionality.Eclipse as a platform for integrating tools
  • SBML links apps
  • Drawing in Powerpoint no meaning impossible to verify no computaitonal analysis not editable sharable.
  • Biopepa has no coupling of software with SBSIVisual – only through SBML file format.Biopepa can simulate stochastically, or can use SBSIVisual’s simulators to simulate as ODEs.
  • Standards – promote tool development E.g., Java as object model -> very standard and well-defined.Need to increase userbase,
  • Having a clear functional model can help with improving the systemE.g., drought-tolerant plants overcoming drug-resistance
  • Eclipse Meets Systems Biology

    1. 1. Eclipse meets Systems BiologyMarch 24th 2010<br />Richard Adams<br />Centre for Systems Biology<br />University of Edinburgh <br />UK<br />
    2. 2. Talk plan<br />What is Systems Biology?<br />What computational approaches are used?<br />How can Eclipse technology help?<br />
    3. 3. Biology occurs across many levels<br />
    4. 4. ~ 20 000 genes<br />2x106protein types<br />> 20 000 metabolites<br />
    5. 5. Microscopy<br />Structural detail<br />Genetics<br />Biochemistry<br />60% metal, 10% wood, 30% plastic <br />Identify important components:<br />Steering wheel, lights, etc.,<br />
    6. 6. ignition<br />engine<br />gears<br />Steering wheel<br />Controlled movement<br />
    7. 7. Aim – to produce quantitative, predictive, computational models<br /> of biological processes.<br />Maths<br />Biology<br />Existing knowledge<br />Static models<br />Kinetic models<br />New knowledge<br />High-throughput data<br />High-resolution data<br />
    8. 8. Example : predicting drug response in breast cancer<br />‘Systems biology reveals new strategies for personalizing cancer medicine and confirms the role PTEN in resistance to trastuzumab’<br />Faratian et al., Cancer Reseach 2009<br />
    9. 9. Systems biology software spectrum<br />Biopepa <br />Edinburgh <br />Pathway Editor <br />Mathematica<br />Biology-specific modelling tools<br />Pathway drawing tools<br />Text-mining/knowledge DBs<br />Matlab <br />1_3_0_RC1_18_3_10<br />Eclipse RCP ?<br /><ul><li> Extensible
    10. 10. customizable
    11. 11. nice UI for biologists
    12. 12. Access to IDEs for computational modellers.</li></ul>- Reusable ready-made components<br />
    13. 13. Biopepa <br />Edinburgh <br />Pathway Editor <br />
    14. 14. What is EPE?<br />A Graphical editor for drawing pathways<br />Why not just use Powerpoint?<br /> - EPE allows export to common systems biology data formats<br /> - multiple graphical notations<br /> - syntax rules for drawing valid diagrams.<br /> - semantic validation.<br />Currently developed by Anatoly Sorokin, Stuart Moodie and <br /> Igor Goryanin, Department of Informatics, University of Edinburgh.<br />
    15. 15.
    16. 16. Overview of Systems Biology Software Infrastructure<br />SBSI <br />clients<br />SBSI Visual <br />✔ Desktop application<br />✔ Upload and edit SBML models<br /><ul><li>Run simulations
    17. 17. Configure optimisations</li></ul>✔ Interact with external repositories<br />✔ Visualisation of data and results<br />SBSI Web <br />Interface<br />✔Command <br /> line<br />SBSI <br />Dispatcher<br />(Task Manager)<br /><ul><li>Compile C codes
    18. 18. Submit jobs to HPC</li></ul>✔Retrieve results<br />✔Provide job status<br />SBSI Numerics<br />Numerical algorithms and <br />Frameworks for <br /><ul><li>Global optimization ✔</li></ul>-Sensitivity analysis<br /><ul><li>Bifurcation analysis</li></ul>core<br />Eddie (ECDF)<br />SBSI repository<br />Models (SBML)<br />Data ( SBSI standard format):<br />-experimental data<br />-simulation results<br />
    19. 19. Running parameter optimisations…<br />Step 1 – create a new SBSI project<br />Editor view allows access to files<br />In the workspace you can <br />store models, data, objective functions and results<br />Data visualization panel<br />
    20. 20. Running parameter optimisations…<br />Step 2 – choose models,<br />data and algorithm type<br /><ul><li>multiple datasets can be selected </li></li></ul><li>Running parameter optimisations…<br />Step 3: choose parameters, constraints and initial values<br />
    21. 21. Running parameter optimisations…<br />Step 4: configure optimization algorithm<br />
    22. 22. Step 5: Configure cost function<br />
    23. 23. Run optimization on server or on background thread… <br />
    24. 24. View Results…<br />Comparison to experimental data<br />Cost function behaviour<br />
    25. 25. Running simulations….<br />Plugins for different SBML based simulators can be added..<br />
    26. 26. BIOPEPA<br />- modelling language based on process algebras<br /> - high level language, can be converted to different<br /> mathematical representations<br /> - can bundle with SBSIVisual or install through update site. <br />
    27. 27. Biopepa stochastic modelling framework integration<br />Biopepa visual editor..<br />BIRT based charting..<br />
    28. 28. Summary<br />
    29. 29. Good features of RCP<br /><ul><li> robust plugin mechanism
    30. 30. Help/update
    31. 31. Workspace (resource handling, Jobs, threading & progress )
    32. 32. UI (wizards, perspectives)
    33. 33. customizability</li></ul> Problematic features of RCP<br /><ul><li> hard to make Project view non-file based (EPE)
    34. 34. P2 update mechanism
    35. 35. GUI testing (SWTBot promising)</li></ul>- Removing unwanted IDE related features<br />
    36. 36. Towards the future? <br />Emergence of standards (file formats, XML schema)<br />Increase user-base & development <br /> Usable, reliable, problem solving software<br /> Publication and citations<br /> Growing awareness – plugin development – community<br /> Coordinated releases? How much collaboration between projects?<br />
    37. 37. SBSI team<br />Core developers<br />Biopepa<br /> Adam Duguid<br />Project management<br />Test Models and <br />Evaluation <br />Requirements &<br /> Numerics <br />Nikos Tsorman<br />Richard Adams<br />Neil Hanlon<br />People previously involved with SBSI<br />Shakir Ali<br />Anatoly Sorokin<br />TreenutSaithong<br />Stuart Moodie<br />Igor Goryanin<br />Alexey Goltsov<br />Galina Lebedeva<br />Circadian clock modellers<br />Azusa Yamaguchi<br />Carl Troein<br />Stephen Gilmore<br /> PI<br />EPCC<br />Andrew Millar<br />Kevin Stratford <br />
    38. 38. Thanks for listening!<br />Any questions ?<br />