PyBioNetFit and the Biological Property Specification Language

Eshan D Mitra; Ryan Suderman; Joshua Colvin; Alexander Ionkov; Andrew Hu; Herbert M Sauro; Richard G Posner; William S Hlavacek

doi:10.1016/j.isci.2019.08.045

PyBioNetFit and the Biological Property Specification Language

iScience. 2019 Sep 27:19:1012-1036. doi: 10.1016/j.isci.2019.08.045. Epub 2019 Aug 28.

Authors

Eshan D Mitra¹, Ryan Suderman¹, Joshua Colvin², Alexander Ionkov¹, Andrew Hu³, Herbert M Sauro³, Richard G Posner², William S Hlavacek⁴

Affiliations

¹ Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA.
² Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA.
³ Department of Bioengineering, University of Washington, Seattle, WA, USA.
⁴ Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA. Electronic address: wish@lanl.gov.

Abstract

In systems biology modeling, important steps include model parameterization, uncertainty quantification, and evaluation of agreement with experimental observations. To help modelers perform these steps, we developed the software PyBioNetFit, which in addition supports checking models against known system properties and solving design problems. PyBioNetFit introduces Biological Property Specification Language (BPSL) for the formal declaration of system properties. BPSL allows qualitative data to be used alone or in combination with quantitative data. PyBioNetFit performs parameterization with parallelized metaheuristic optimization algorithms that work directly with existing model definition standards: BioNetGen Language (BNGL) and Systems Biology Markup Language (SBML). We demonstrate PyBioNetFit's capabilities by solving various example problems, including the challenging problem of parameterizing a 153-parameter model of cell cycle control in yeast based on both quantitative and qualitative data. We demonstrate the model checking and design applications of PyBioNetFit and BPSL by analyzing a model of targeted drug interventions in autophagy signaling.

Keywords: Bioinformatics; Biological Sciences; Complex Systems; Computer Science; Parallel System; Systems Biology.

Abstract

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