Python unleashed on systems biology

Christopher R. Myers, Ryan N. Gutenkunst, James P. Sethna

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Cornell University has developed an open source software system called SloppyCell, written in Python, to model biomolecular reaction networks. SloppyCell improves standard dynamical modeling by focusing on inference of model parameters from data and quantification of the uncertainties of model prediction. An important role in the software is to combine together many diverse modules that provide specific functionality. NumPy and SciPy were used for numeric, particularly for integrating differential equations, optimizing parameters by least squares fits to data, and analyzing the Hessian matrix about a best-fit set of parameters. Models are read and written in a standardized XML-based file format and the Systems Biology Markup Language (SBML) with assistance from a Python interface to the libSBML library.

Original languageEnglish (US)
Article number4160253
Pages (from-to)34-37
Number of pages4
JournalComputing in Science and Engineering
Volume9
Issue number3
DOIs
StatePublished - May 2007
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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