Presentation given at Monash University on 19 August 2013.

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