Programmatic modeling for biological systems.


Journal

Current opinion in systems biology
ISSN: 2452-3100
Titre abrégé: Curr Opin Syst Biol
Pays: England
ID NLM: 101698476

Informations de publication

Date de publication:
Sep 2021
Historique:
entrez: 6 9 2021
pubmed: 7 9 2021
medline: 7 9 2021
Statut: ppublish

Résumé

Computational modeling has become an established technique to encode mathematical representations of cellular processes and gain mechanistic insights that drive testable predictions. These models are often constructed using graphical user interfaces or domain-specific languages, with community standards used for interchange. Models undergo steady state or dynamic analysis, which can include simulation and calibration within a single application, or transfer across various tools. Here, we describe a novel programmatic modeling paradigm, whereby modeling is augmented with software engineering best practices. We focus on Python - a popular programming language with a large scientific package ecosystem. Models can be encoded as programs, adding benefits such as modularity, testing, and automated documentation generators, while still being extensible and exportable to standardized formats for use with external tools if desired. Programmatic modeling is a key technology to enable collaborative model development and enhance dissemination, transparency, and reproducibility.

Identifiants

pubmed: 34485764
doi: 10.1016/j.coisb.2021.05.004
pmc: PMC8411905
mid: NIHMS1708200
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : NCI NIH HHS
ID : U01 CA215845
Pays : United States
Organisme : NCI NIH HHS
ID : U54 CA217450
Pays : United States

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Auteurs

Alexander L R Lubbock (ALR)

Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37212, United States of America.
Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville Tennessee 37212, United States of America.

Carlos F Lopez (CF)

Department of Biochemistry, Vanderbilt University, Nashville, Tennessee 37212, United States of America.
Vanderbilt-Ingram Cancer Center, Vanderbilt University, Nashville Tennessee 37212, United States of America.
Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee 37212, United States of America.

Classifications MeSH