The systems biology simulation core library

Author:

Panchiwala Hemil1ORCID,Shah Shalin23ORCID,Planatscher Hannes4ORCID,Zakharchuk Mykola5ORCID,König Matthias6ORCID,Dräger Andreas5789ORCID

Affiliation:

1. Department of Computer Science and Engineering, Indian Institute of Technology, Roorkee, IN 247667, USA

2. Department of Electrical and Computer Engineering, Duke University, Durham, NC 27701, USA

3. Bloomberg, New York, NY 10022, USA

4. Signatope GmbH, Reutlingen 72770, Germany

5. Department of Computer Science, University of Tübingen, Tübingen 72076, Germany

6. Institute for Theoretical Biology, Humboldt University of Berlin, Berlin 10115, Germany

7. Computational Systems Biology of Infections and Antimicrobial-Resistant Pathogens, Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen 72076, Germany

8. German Center for Infection Research (DZIF), Partner Site Tübingen, Tübingen 72076, Germany

9. Cluster of Excellence ‘Controlling Microbes to Fight Infections,’ University of Tübingen, Tübingen 72076, Germany

Abstract

Abstract Summary Studying biological systems generally relies on computational modeling and simulation, e.g., model-driven discovery and hypothesis testing. Progress in standardization efforts led to the development of interrelated file formats to exchange and reuse models in systems biology, such as SBML, the Simulation Experiment Description Markup Language (SED-ML) or the Open Modeling EXchange format. Conducting simulation experiments based on these formats requires efficient and reusable implementations to make them accessible to the broader scientific community and to ensure the reproducibility of the results. The Systems Biology Simulation Core Library (SBSCL) provides interpreters and solvers for these standards as a versatile open-source API in JavaTM. The library simulates even complex bio-models and supports deterministic Ordinary Differential Equations; Stochastic Differential Equations; constraint-based analyses; recent SBML and SED-ML versions; exchange of results, and visualization of in silico experiments; open modeling exchange formats (COMBINE archives); hierarchically structured models; and compatibility with standard testing systems, including the Systems Biology Test Suite and published models from the BioModels and BiGG databases. Availability and implementation SBSCL is freely available at https://draeger-lab.github.io/SBSCL/ and via Maven Central. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

The National Resource for Network Biology (NRNB) and Google Inc

German Center for Infection Research

German Research Foundation

Cluster of Excellence EXC 2124 Controlling Microbes to Fight Infections

Federal Ministry of Education and Research

Systems Medicine of the Liver [LiSyM

DFG within the Research Unit Programme

Complex Resection—A Systems Medicine Approach)

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference8 articles.

1. COMBINE archive and OMEX format: one file to share all information to reproduce a modeling project;Bergmann;BMC Bioinformatics,2014

2. FERN – a Java framework for stochastic simulation and evaluation of reaction networks;Erhard;BMC Bioinformatics,2008

3. SBML Level 3: an extensible format for the exchange and reuse of biological models;Keating;Mol. Syst. Biol,2020

4. The systems biology simulation core algorithm;Keller;BMC Syst. Biol,2013

5. BioModels—15 years of sharing computational models in life science;Malik-Sheriff;Nucleic Acids Res,2020

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