Literature DB >> 23715986

BioModels Database: a repository of mathematical models of biological processes.

Vijayalakshmi Chelliah1, Camille Laibe, Nicolas Le Novère.   

Abstract

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

Mesh:

Year:  2013        PMID: 23715986     DOI: 10.1007/978-1-62703-450-0_10

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  49 in total

Review 1.  Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability.

Authors:  Anil Kumar; Rajesh Kumar Pathak; Sanjay Mohan Gupta; Vikram Singh Gaur; Dinesh Pandey
Journal:  OMICS       Date:  2015-10

Review 2.  Publishing 13C metabolic flux analysis studies: a review and future perspectives.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2013-09-08       Impact factor: 9.783

Review 3.  Modeling for (physical) biologists: an introduction to the rule-based approach.

Authors:  Lily A Chylek; Leonard A Harris; James R Faeder; William S Hlavacek
Journal:  Phys Biol       Date:  2015-07-16       Impact factor: 2.583

Review 4.  Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Authors:  Lily A Chylek; Leonard A Harris; Chang-Shung Tung; James R Faeder; Carlos F Lopez; William S Hlavacek
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-09-30

5.  Scaling methods for accelerating kinetic Monte Carlo simulations of chemical reaction networks.

Authors:  Yen Ting Lin; Song Feng; William S Hlavacek
Journal:  J Chem Phys       Date:  2019-06-28       Impact factor: 3.488

Review 6.  Design Automation in Synthetic Biology.

Authors:  Evan Appleton; Curtis Madsen; Nicholas Roehner; Douglas Densmore
Journal:  Cold Spring Harb Perspect Biol       Date:  2017-04-03       Impact factor: 10.005

7.  Modeling heterogeneous tumor growth dynamics and cell-cell interactions at single-cell and cell-population resolution.

Authors:  Leonard A Harris; Samantha Beik; Patricia M M Ozawa; Lizandra Jimenez; Alissa M Weaver
Journal:  Curr Opin Syst Biol       Date:  2019-09-16

8.  An integrative modeling framework reveals plasticity of TGF-β signaling.

Authors:  Geoffroy Andrieux; Michel Le Borgne; Nathalie Théret
Journal:  BMC Syst Biol       Date:  2014-03-12

9.  Downregulated UCHL1 Accelerates Gentamicin-Induced Auditory Cell Death via Autophagy.

Authors:  Yeon Ju Kim; Kyung Kim; Yun Yeong Lee; Oak-Sung Choo; Jeong Hun Jang; Yun-Hoon Choung
Journal:  Mol Neurobiol       Date:  2019-04-30       Impact factor: 5.590

10.  Use of mechanistic models to integrate and analyze multiple proteomic datasets.

Authors:  Edward C Stites; Meraj Aziz; Matthew S Creamer; Daniel D Von Hoff; Richard G Posner; William S Hlavacek
Journal:  Biophys J       Date:  2015-04-07       Impact factor: 4.033

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