BEL2ABM: agent-based simulation of static models in Biological Expression Language

Michaela Gündel; Charles Tapley Hoyt; Martin Hofmann-Apitius

doi:10.1093/bioinformatics/bty107

BEL2ABM: agent-based simulation of static models in Biological Expression Language

Bioinformatics. 2018 Jul 1;34(13):2316-2318. doi: 10.1093/bioinformatics/bty107.

Authors

Michaela Gündel^{1

2}, Charles Tapley Hoyt^{1

2}, Martin Hofmann-Apitius^{1

2}

Affiliations

¹ Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
² Department of Life Science Informatics, Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany.

Abstract

Summary: While cause-and-effect knowledge assembly models encoded in Biological Expression Language are able to support generation of mechanistic hypotheses, they are static and limited in their ability to encode temporality. Here, we present BEL2ABM, a software for producing continuous, dynamic, executable agent-based models from BEL templates.

Availability and implementation: The tool has been developed in Java and NetLogo. Code, data and documentation are available under the Apache 2.0 License at https://github.com/pybel/bel2abm.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Documentation
Humans
Language*
Models, Biological
Software*