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Programming with models: modularity and abstraction provide powerful capabilities for systems biology

Mallavarapu, Aneil and Thomson, Matthew and Ullian, Benjamin and Gunawardena, Jeremy (2009) Programming with models: modularity and abstraction provide powerful capabilities for systems biology. Journal of the Royal Society Interface, 6 (32). pp. 257-270. ISSN 1742-5689. PMCID PMC2659579. https://resolver.caltech.edu/CaltechAUTHORS:20170206-154848804

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Abstract

Mathematical models are increasingly used to understand how phenotypes emerge from systems of molecular interactions. However, their current construction as monolithic sets of equations presents a fundamental barrier to progress. Overcoming this requires modularity, enabling sub-systems to be specified independently and combined incrementally, and abstraction, enabling generic properties of biological processes to be specified independently of specific instances. These, in turn, require models to be represented as programs rather than as datatypes. Programmable modularity and abstraction enables libraries of modules to be created, which can be instantiated and reused repeatedly in different contexts with different components. We have developed a computational infrastructure that accomplishes this. We show here why such capabilities are needed, what is required to implement them and what can be accomplished with them that could not be done previously.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1098/rsif.2008.0205DOIArticle
http://rsif.royalsocietypublishing.org/content/6/32/257PublisherArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2659579/PubMed CentralArticle
Additional Information:© 2008 The Royal Society. Received May 15, 2008. Accepted June 20, 2008. We are grateful to the Bauer Center for Genomics Research and to Craig Muir for support during the initial phase of this work. We thank, especially, Steve Harrison, Ed Harlow, Marc Kirschner and Rebecca Ward of the Harvard Medical School for enabling this work to come to fruition through their support for the Virtual Cell Program. We thank Peter Lawrence for the Drosophila image in figure 6a, Radhika Nagpal for access to material in press, David Young for his open source implementation of LISA and Dave Fox of LispWorks for his assistance with the Lisp environment. We thank Carl Pabo, Brian Seed and Rebecca Ward for their insightful comments and the other members of the Virtual Cell Program for their assistance. The authors declare that they have no competing financial interests.
Subject Keywords:model building; systems biology; modularity; abstraction
Issue or Number:32
PubMed Central ID:PMC2659579
Record Number:CaltechAUTHORS:20170206-154848804
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170206-154848804
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:74110
Collection:CaltechAUTHORS
Deposited By: Donna Wrublewski
Deposited On:18 Feb 2017 04:02
Last Modified:03 Oct 2019 16:34

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