TY - JOUR
T1 - Python unleashed on systems biology
AU - Myers, Christopher R.
AU - Gutenkunst, Ryan N.
AU - Sethna, James P.
N1 - Funding Information:
We thank Fergal Casey, Joshua Waterfall, Robert Kuczenski, and Jordan Atlas for their help in developing and testing SloppyCell, and we acknowledge the insights of Kevin Brown and Colin Hill in developing predecessor codes, which have helped motivate our work. Development of SloppyCell has been supported by NSF grant DMR-0218475, USDA-ARS project 1907-21000-017-05, and an NIH Molecular Biophysics Training grant to Gutenkunst (no. T32-GM-08267).
PY - 2007/5
Y1 - 2007/5
N2 - 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.
AB - 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.
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U2 - 10.1109/MCSE.2007.60
DO - 10.1109/MCSE.2007.60
M3 - Article
AN - SCOPUS:34247473881
SN - 1521-9615
VL - 9
SP - 34
EP - 37
JO - Computing in Science and Engineering
JF - Computing in Science and Engineering
IS - 3
M1 - 4160253
ER -