systems biology systems
DESCRIPTION
Presentation given at Monash University on 19 August 2013.TRANSCRIPT
Systems Biology Systems
Michael Hucka, Ph.D.Department of Computing + Mathematical Sciences
California Institute of TechnologyPasadena, CA, USA
Monash University, Australia, August 2013
Email: [email protected] Twitter: @mhucka
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The early days of Systems Biology
The SBW and SBML projects
In hindsight ...
Outli
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The early days of Systems Biology
The SBW and SBML projects
In hindsight ...
Thread #1: criticisms of molecular biology at the timeMolecular 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
(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)
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”
Thread #2: systems modelingEarly 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
Subsequent developments in systems theoryBiology:
• 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
Fast & cheap computing changed everythingEarly 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”
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 helpif applied in service of understanding the results of experiments
Together, the two threads can weave a tapestry of understanding
Of course, community-building is not quite that easyRequired 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)
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The early days of Systems Biology
The SBW and SBML projects
In hindsight ...
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
Existing software was not interoperable
SBML: a lingua fra
nca
for software
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 <Beginning of SBML model definition>
List of function definitionsList of unit definitionsList of compartments
List of molecular speciesList of parameters
List of rulesList of reactions
List of events<End of SBML model definition>
SBML = Systems Biology Markup Language
The raw SBML (as XML)
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 inBioModels Databasehttp://biomodels.net/biomodels
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
7000 reactionsThiele et al., Nature Biotech., 31, 2013
Many significant and popular models are in SBML form
Where to find out more: SBML.org
Essential ingredients of the effortOur 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
Essential ingredients of the effortOur 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
Essential ingredients of the effortOur 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
The most important outcome?
A community flourishedAttendees at SBML 10th Anniversary Symposium, Edinburgh, 2010
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
Outli
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The early days of Systems Biology
The SBW and SBML projects
In hindsight ...
What did we get right and wrong?
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
National Institute of General Medical Sciences (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 AgricultureJapanese 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:
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
Was it worth it?
There are tradeoffsThis 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
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 communityAttendees 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
Original PI’s:
SBML Team:
SBML Editors:
BioModels DB:
Mike Hucka, Nicolas Le Novère, Sarah Keating, Frank Bergmann, Lucian Smith, Chris Myers, Stefan Hoops, Sven Sahle, James Schaff, Darren Wilkinson
And a huge thanks to many others in the COMBINE community
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
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