Literature DB >> 24713438

MetDisease--connecting metabolites to diseases via literature.

William Duren1, Terry Weymouth1, Tim Hull1, Gilbert S Omenn1, Brian Athey1, Charles Burant1, Alla Karnovsky1.   

Abstract

MOTIVATION: In recent years, metabolomics has emerged as an approach to perform large-scale characterization of small molecules in biological systems. Metabolomics posed a number of bioinformatics challenges associated in data analysis and interpretation. Genome-based metabolic reconstructions have established a powerful framework for connecting metabolites to genes through metabolic reactions and enzymes that catalyze them. Pathway databases and bioinformatics tools that use this framework have proven to be useful for annotating experimental metabolomics data. This framework can be used to infer connections between metabolites and diseases through annotated disease genes. However, only about half of experimentally detected metabolites can be mapped to canonical metabolic pathways. We present a new Cytoscape 3 plug-in, MetDisease, which uses an alternative approach to link metabolites to disease information. MetDisease uses Medical Subject Headings (MeSH) disease terms mapped to PubChem compounds through literature to annotate compound networks.
AVAILABILITY AND IMPLEMENTATION: MetDisease can be downloaded from http://apps.cytoscape.org/apps/metdisease or installed via the Cytoscape app manager. Further information about MetDisease can be found at http://metdisease.ncibi.org CONTACT: akarnovs@med.umich.edu SUPPLEMENTARY INFORMATION: Supplementary Data are available at Bioinformatics online.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mesh:

Year:  2014        PMID: 24713438      PMCID: PMC4103594          DOI: 10.1093/bioinformatics/btu179

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  20 in total

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  12 in total

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Review 2.  Metabolomics and diabetes: analytical and computational approaches.

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Review 3.  Integrating bioinformatics approaches for a comprehensive interpretation of metabolomics datasets.

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4.  Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

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5.  Metabolomics of ApcMin/+ mice genetically susceptible to intestinal cancer.

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6.  The Saliva Exposome for Monitoring of Individuals' Health Trajectories.

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8.  Multi-Platform Metabolomics Analyses Revealed the Complexity of Serum Metabolites in LPS-Induced Neuroinflammed Rats Treated with Clinacanthus nutans Aqueous Extract.

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Journal:  Front Pharmacol       Date:  2021-06-09       Impact factor: 5.810

Review 9.  Systems Medicine as an Emerging Tool for Cardiovascular Genetics.

Authors:  Tina Haase; Daniela Börnigen; Christian Müller; Tanja Zeller
Journal:  Front Cardiovasc Med       Date:  2016-08-30

10.  A global lipid map defines a network essential for Zika virus replication.

Authors:  Hans C Leier; Jules B Weinstein; Jennifer E Kyle; Joon-Yong Lee; Lisa M Bramer; Kelly G Stratton; Douglas Kempthorne; Aaron R Navratil; Endale G Tafesse; Thorsten Hornemann; William B Messer; Edward A Dennis; Thomas O Metz; Eric Barklis; Fikadu G Tafesse
Journal:  Nat Commun       Date:  2020-07-21       Impact factor: 14.919

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