Dataset Information

Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications.

ABSTRACT: Biological network models offer a framework for understanding disease by describing the relationships between the mechanisms involved in the regulation of biological processes. Crowdsourcing can efficiently gather feedback from a wide audience with varying expertise. In the Network Verification Challenge, scientists verified and enhanced a set of 46 biological networks relevant to lung and chronic obstructive pulmonary disease. The networks were built using Biological Expression Language and contain detailed information for each node and edge, including supporting evidence from the literature. Network scoring of public transcriptomics data inferred perturbation of a subset of mechanisms and networks that matched the measured outcomes. These results, based on a computable network approach, can be used to identify novel mechanisms activated in disease, quantitatively compare different treatments and time points, and allow for assessment of data with low signal. These networks are periodically verified by the crowd to maintain an up-to-date suite of networks for toxicology and drug discovery applications.

SUBMITTER: sbv IMPROVER project team and challenge best performers

PROVIDER: S-EPMC4944831 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications.

Namasivayam Aishwarya Alex AA Morales Alejandro Ferreiro AF Lacave Ángela María Fajardo ÁM Tallam Aravind A Simovic Borislav B Alfaro David Garrido DG Bobbili Dheeraj Reddy DR Martin Florian F Androsova Ganna G Shvydchenko Irina I Park Jennifer J Calvo Jorge Val JV Hoeng Julia J Peitsch Manuel C MC Racero Manuel González Vélez MG Biryukov Maria M Talikka Marja M Pérez Modesto Berraquero MB Rohatgi Neha N Díaz-Díaz Noberto N Mandarapu Rajesh R Ruiz Rubén Amián RA Davidyan Sergey S Narayanasamy Shaman S Boué Stéphanie S Guryanova Svetlana S Arbas Susana Martínez SM Menon Swapna S Xiang Yang Y

Gene regulation and systems biology 20160712

Biological network models offer a framework for understanding disease by describing the relationships between the mechanisms involved in the regulation of biological processes. Crowdsourcing can efficiently gather feedback from a wide audience with varying expertise. In the Network Verification Challenge, scientists verified and enhanced a set of 46 biological networks relevant to lung and chronic obstructive pulmonary disease. The networks were built using Biological Expression Language and con ...[more]

PMID: 27429547

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Dataset Information

Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications.

Publications

Community-Reviewed Biological Network Models for Toxicology and Drug Discovery Applications.

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