Systems Biology Systems

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Presentation given at Monash University on 19 August 2013.

Presentation given at Monash University on 19 August 2013.

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  • 1. Systems Biology Systems Michael Hucka, Ph.D. Department of Computing + Mathematical Sciences California Institute of Technology Pasadena, CA, USA Monash University, Australia, August 2013 Email: mhucka@caltech.edu Twitter: @mhucka
  • 2. Outline The early days of Systems Biology The SBW and SBML projects In hindsight ...
  • 3. Outline The early days of Systems Biology The SBW and SBML projects In hindsight ...
  • 4. Thread #1: criticisms of molecular biology at the time Molecular biology approach characterized as reductionist: • Catalogue and characterize all the parts • Expectation: knowledge of all parts understanding the system Some typical methods: • Identification of proteins, sequencing genome • Knock-out experiments • Drawing diagrams Dissatisfaction: too many questions left unanswered • E.g.: have sequences, yet don’t know roles of most genes
  • 5. (Not entirely accurate, nor fair) Many people understood it wouldn’t itself yield deep understanding • And molecular biology does have history of integrative thinking - 1950’s, 1960’s: feedback inhibition, lac operon, others (And anyway, systems biology needed molecular biology)
  • 6. Genomics science = systems biology? A scaling up of experimental approaches to whole genomes, made possible by high-throughput technologies • Catalogue and characterize parts and interactions The dawn of the many system-wide“omics” • Transcriptomics, proteomics, metabolomics, ... “Lee Hood brand of systems biology”
  • 7. Thread #2: systems modeling Early systems thinkers • Bogdanov (1910-1920s?), Wiener (1950’s), Mesarovic (1960’s), von Bertalanffy (1960’s) • Articulated the idea that understanding the system is critical - “The whole is more than the sum of its parts” • Model-centric view: build models to help understanding But: much early work was too removed from real biology • Engineers and physicists dabbling in biology • Mainstream biology ignored it
  • 8. Subsequent developments in systems theory Biology: • Early successes in application of mathematical modeling: - Hodgkin & Huxley (1952): neuronal action potential - Noble (1960): heart • New theoretical approaches (1960s-1970s) - Metabolic Control Analysis - Biochemical Systems Theory Engineering: • Advances in control theory and dynamical systems theory Common theme: complex systems are nonlinear, with feedback loops
  • 9. Fast & cheap computing changed everything Early simulation work in biology in 1940-1960’s was difficult, limited • E.g., Chance (on analog computers!), Garfinkel Rapid advances in computing (1980-1990’s) revolutionized simulation • Could simulate larger, more complex models, with nonlinearities and feedback mechanisms • Computing environments became more sophisticated and friendly Of course, the computing revolution also enabled high-throughput bio. • ... which led to the need to interpret massive quantities of data • ... which led to reexamination of engineering-based ideas - Dynamical behavior, control systems, etc. “Hiroaki Kitano brand of systems biology”
  • 10. Systems biology is both threads Early dichotomy gave way to realization that both are needed And both need each other • Data about components (via omics) are needed, but alone do not explain function and behavior • Math/engineering concepts (control systems, feedback, etc.) only help if applied in service of understanding the results of experiments Together, the two threads can weave a tapestry of understanding
  • 11. Of course, community-building is not quite that easy Required active efforts, particularly on the part of Hiroaki Kitano How did he achieve such influence? • Timing • Convincing other influential thinkers • Building an identity - Publishing influential papers - Organizing conferences (ICSB) - Founding an institute (SBI)
  • 12. Outline The early days of Systems Biology The SBW and SBML projects In hindsight ...
  • 13. 2000:The year we made contact One initial goal: get 8–10 software systems interacting (Gepasi, DBsolve, StochSim, ...) John DoyleHiroaki Kitano Hamid Bolouri Andrew Finney Herbert Sauro Mike Hucka JST ERATO Kitano Symbiotic Systems Project
  • 14. Existing software was not interoperable
  • 15. SBML:alinguafranca forsoftware
  • 16. Format for representing computational models of biological processes • Data structures + usage principles + serialization to XML • (Mostly) Declarative, not procedural—not a scripting language Neutral with respect to modeling framework • E.g., ODE, stochastic systems, etc. Important: software reads/writes SBML, not humans SBML = Systems Biology Markup Language
  • 17. The raw SBML (as XML)
  • 18. Many models can be encoded • Metabolic network models • Signaling pathway models • Conductance-based models • Neural models • Pharmacokinetic/dynamics models • Infectious diseases New types supported by SBML Level 3 packages • Flux balance constraints • Qualitative models • ... more in the works Scope of SBML encompasses many types of models Find examples in BioModels Databasehttp://biomodels.net/biomodels
  • 19. Many software systems support SBML today 0 100 200 300 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 (number of tools in the guide, counted in middle of each year) 254+ today
  • 20. 7000 reactionsThiele et al., Nature Biotech., 31, 2013 Many significant and popular models are in SBML form
  • 21. Where to find out more: SBML.org
  • 22. Essential ingredients of the effort Our core values were formulated by Hamid Bolouri: • Our goal was not to replace the systems others were developing— our goal was to add value to their work • We made software tools available, for many platforms • We made all our work licensed as open source and free of charge We provided a focus for people to discuss standards and software • We organized and hosted workshops. Lots of workshops. Lots. • We listened to others and formulated solutions in response to their requests, and solicited constant feedback
  • 23. Essential ingredients of the effort Our core values were formulated by Hamid Bolouri: • Our goal was not to replace the systems others were developing— our goal was to add value to their work • We made software tools available, for many environments • We made all our work licensed as open source and free of charge
  • 24. Essential ingredients of the effort Our core values were formulated by Hamid Bolouri: Our goal was not to replace the systems others were developing— our goal was to add value to their work We made software tools available, for many environments We made all our work licensed as open source and free of charge We provided a focus for people to discuss standards and software • We organized and hosted workshops. Lots of workshops. Lots. • We listened to others and formulated solutions in response to their requests, and solicited constant feedback
  • 25. The most important outcome?
  • 26. A community flourished Attendees at SBML 10th Anniversary Symposium, Edinburgh, 2010
  • 27. More agreement needs to be achieved, for additional facets of modeling Numerous bottom-up efforts have self-organized • Some overlapped, yet proceeded independently Several groups realized the situation was not constructive • Result: COMBINE – Computational Modeling in Biology Network Main objectives: • Coordinate meetings • Harmonize standards development • Develop standard operating procedures and common tools • Provide a recognized voice Later: the creation of COMBINE
  • 28. Outline The early days of Systems Biology The SBW and SBML projects In hindsight ...
  • 29. What did we get right and wrong?
  • 30. Time it well • Too early and too late are bad Start with actual stakeholders • Address real needs, not perceived ones Start with small team of dedicated developers • Can work faster, more focused; also avoids“designed-by-committee” Engage people constantly, in many ways • Electronic forums, email, electronic voting, surveys, hackathons Make the results free and open-source • Makes people comfortable knowing it will always be available Be creative about seeking funding Some things we (maybe?) got right
  • 31. NationalInstituteofGeneralMedicalSciences(USA) European Molecular Biology Laboratory (EMBL) JST ERATO Kitano Symbiotic Systems Project (Japan) (to 2003) JST ERATO-SORST Program (Japan) ELIXIR (UK) Beckman Institute, Caltech (USA) Keio University (Japan) International Joint Research Program of NEDO (Japan) Japanese Ministry of Agriculture Japanese Ministry of Educ., Culture, Sports, Science and Tech. BBSRC (UK) National Science Foundation (USA) DARPA IPTO Bio-SPICE Bio-Computation Program (USA) Air Force Office of Scientific Research (USA) STRI, University of Hertfordshire (UK) Molecular Sciences Institute (USA) SBML was made possible thanks to funding from:
  • 32. Not waiting for implementations before freezing specifications • Sometimes finalized specification before implementations tested it - Especially bad when we failed to do a good job ‣ E.g.,“forward thinking”features, or“elegant”designs Not formalizing the development process sufficiently • Especially early in the history, did not have a very open process Not resolving intellectual property issues from the beginning • Industrial users ask“who has the right to give any rights to this?” Some things we certainly got wrong
  • 33. Was it worth it?
  • 34. There are tradeoffs This was not the path I planned when I did my Ph.D. • It’s been nice, but ... Developing usable software ≠ developing research-grade software • Takes huge amounts of time - That’s time you are not writing papers ‣ Remember it’s still publish or perish ... Ultimately must decide if you really want the life of a professor
  • 35. Nicolas Le Novère, Henning Hermjakob, Camille Laibe, Chen Li, Lukas Endler, Nico Rodriguez, Marco Donizelli,Viji Chelliah, Mélanie Courtot, Harish Dharuri This work was made possible thanks to a great community Attendees at SBML 10th Anniversary Symposium, Edinburgh, 2010 John C. Doyle, Hiroaki Kitano Mike Hucka, Sarah Keating, Frank Bergmann, Lucian Smith, Andrew Finney, Herbert Sauro, Hamid Bolouri, Ben Bornstein, Bruce Shapiro, Akira Funahashi, Akiya Juraku, Ben Kovitz OriginalPI’s: SBMLTeam: SBMLEditors: BioModelsDB: Mike Hucka, Nicolas Le Novère, Sarah Keating, Frank Bergmann, Lucian Smith, Chris Myers, Stefan Hoops, Sven Sahle, James Schaff, DarrenWilkinson And a huge thanks to many others in the COMBINE community
  • 36. SBML http://sbml.org BioModels Database http://biomodels.net/biomodels MIRIAM http://biomodels.net/miriam identifiers.org http://identifiers.org SED-ML http://biomodels.net/sed-ml SBO http://biomodels.net/sbo SBGN http://sbgn.org COMBINE http://co.mbine.org URLs
  • 37. I’d like your feedback! You can use this anonymous form: http://tinyurl.com/mhuckafeedback