PyBioNetFit and the Biological Property Specification Language

被引:31
作者
Mitra, Eshan D. [1 ]
Suderman, Ryan [1 ,4 ]
Colvin, Joshua [2 ]
Lonkov, Alexander [1 ,5 ]
Hu, Andrew [3 ]
Sauro, Herbert M. [3 ]
Posner, Richard G. [2 ]
Hlavacek, William S. [1 ]
机构
[1] Los Alamos Natl Lab, Div Theoret, Theoret Biol & Biophys Grp, Los Alamos, NM 87545 USA
[2] No Arizona Univ, Dept Biol Sci, Box 5640}, Flagstaff, AZ 86011 USA
[3] Univ Washington, Dept Bioengn, Seattle, WA 98195 USA
[4] Immunetrics, Pittsburgh, PA USA
[5] Univ Wisconsin, Madison, WI USA
基金
美国国家卫生研究院;
关键词
SYSTEMS BIOLOGY; DIFFERENTIAL EVOLUTION; PARAMETER-ESTIMATION; SENSITIVITY ANALYSIS; KINETIC-ANALYSIS; SCATTER SEARCH; EARLY EVENTS; MODEL; PHOSPHORYLATION; ALGORITHMS;
D O I
10.1016/j.isci.2019.08.045
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:1012 / +
页数:32
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