ABC-SysBio-approximate Bayesian computation in Python with GPU support

作者：Liepe Juliane; Barnes Chris^*; Cule Erika; Erguler Kamil; Kirk Paul; Toni Tina; Stumpf Michael P H

来源：Bioinformatics, 2010, 26(14): 1797-1799.

DOI：10.1093/bioinformatics/btq278

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions.
Results: Here we present a Python package, ABC-SysBio, that implements parameter inference and model selection for dynamical systems in an approximate Bayesian computation (ABC) framework. ABC-SysBio combines three algorithms: ABC rejection sampler, ABC SMC for parameter inference and ABC SMC for model selection. It is designed to work with models written in Systems Biology Markup Language (SBML). Deterministic and stochastic models can be analyzed in ABC-SysBio.

• 出版日期2010-7-15
• 单位上海生物信息技术研究中心