BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

Thomas, Brandon R.; Chylek, Lily A.; Colvin, Joshua; Sirimulla, Suman; Clayton, Andrew H. A.; Hlavacek, William S.; Posner, Richard G.

doi:10.1093/bioinformatics/btv655

Title: BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

Abstract

Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.

Authors:

Thomas, Brandon R. ^[1]; Chylek, Lily A. ^[2]; Colvin, Joshua ^[1]; Sirimulla, Suman ^[3]; Clayton, Andrew H. A. ^[4]; Hlavacek, William S. ^[5]; Posner, Richard G. ^[1]

Northern Arizona Univ., Flagstaff, AZ (United States). Dept. of Biological Sciences
Cornell Univ., Ithaca, NY (United States). Baker Lab., Dept. of Chemistry and Chemical Biology; Northern Arizona Univ., Flagstaff, AZ (United States). Dept. of Biological Sciences
Saint Louis College of Pharmacy, Saint Louis, MO (United States). Dept. of Basic Sciences
Swinburne Univ. of Technology, Hawthorn, VIC (Australia). Center for Microphotonics, Faculty of Science, Engineering and Technology, Cell Biophysics Lab.
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Publication Date:: Mon Nov 09 00:00:00 EST 2015

Research Org.:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Org.:: Work for Others (WFO); National Institutes of Heath (NIH); USDOE

OSTI Identifier:: 1406198

Report Number(s):: LA-UR-15-25157
Journal ID: ISSN 1367-4803

Grant/Contract Number:: AC52-06NA25396; R01GM111510

Resource Type:: Accepted Manuscript

Journal Name:: Bioinformatics

Additional Journal Information:: Journal Volume: 32; Journal Issue: 5; Journal ID: ISSN 1367-4803

Publisher:: Oxford University Press

Country of Publication:: United States

Language:: English

Subject:: 60 APPLIED LIFE SCIENCES; 59 BASIC BIOLOGICAL SCIENCES; Biological Science

Citation Formats


                    Thomas, Brandon R., Chylek, Lily A., Colvin, Joshua, Sirimulla, Suman, Clayton, Andrew H. A., Hlavacek, William S., and Posner, Richard G. BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.  United States: N. p., 2015. 
Web.  doi:10.1093/bioinformatics/btv655.

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                    Thomas, Brandon R., Chylek, Lily A., Colvin, Joshua, Sirimulla, Suman, Clayton, Andrew H. A., Hlavacek, William S., & Posner, Richard G. BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments.  United States.  https://doi.org/10.1093/bioinformatics/btv655

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                    Thomas, Brandon R., Chylek, Lily A., Colvin, Joshua, Sirimulla, Suman, Clayton, Andrew H. A., Hlavacek, William S., and Posner, Richard G. Mon .  
"BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments".  United States.  https://doi.org/10.1093/bioinformatics/btv655.  https://www.osti.gov/servlets/purl/1406198.

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@article{osti_1406198,

  title        = {BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments},

  author       = {Thomas, Brandon R. and Chylek, Lily A. and Colvin, Joshua and Sirimulla, Suman and Clayton, Andrew H. A. and Hlavacek, William S. and Posner, Richard G.},

  abstractNote = {Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here in this paper, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive.},

  doi          = {10.1093/bioinformatics/btv655},

  journal      = {Bioinformatics},

  number       = 5,

  volume       = 32,

  place        = {United States},

  year         = {Mon Nov 09 00:00:00 EST 2015},

  month        = {Mon Nov 09 00:00:00 EST 2015}

}

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Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor
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Erickson, Keesha E.; Rukhlenko, Oleksii S.; Shahinuzzaman, Md
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Title: BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

Abstract

Citation Formats

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Using both qualitative and quantitative data in parameter identification for systems biology models
journal, September 2018

Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks
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BioNetGen 2.2: advances in rule-based modeling
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Revealing dynamic regulations and the related key proteins of myeloma-initiating cells by integrating experimental data into a systems biological model
journal, July 2019

Intrinsic limits of information transmission in biochemical signalling motifs
journal, October 2018

Modeling cell line-specific recruitment of signaling proteins to the insulin-like growth factor 1 receptor
journal, January 2019

From word models to executable models of signaling networks using automated assembly
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Allergen Valency, Dose, and FcεRI Occupancy Set Thresholds for Secretory Responses to Pen a 1 and Motivate Design of Hypoallergens
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