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