Dataset Information

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

ABSTRACT:

Motivation

Capabilities in the field of metabolomics have grown tremendously in recent years. Many existing resources contain the chemical properties and classifications of commonly identified metabolites. However, the annotation of small molecules (both endogenous and synthetic) to meaningful biological pathways and concepts still lags behind the analytical capabilities and the chemistry-based annotations. Furthermore, no tools are available to visually explore relationships and networks among functionally related groups of metabolites (biomedical concepts). Such a tool would provide the ability to establish testable hypotheses regarding links among metabolic pathways, cellular processes, phenotypes and diseases.

Results

Here we present ConceptMetab, an interactive web-based tool for mapping and exploring the relationships among 16 069 biologically defined metabolite sets developed from Gene Ontology, KEGG and Medical Subject Headings, using both KEGG and PubChem compound identifiers, and based on statistical tests for association. We demonstrate the utility of ConceptMetab with multiple scenarios, showing it can be used to identify known and potentially novel relationships among metabolic pathways, cellular processes, phenotypes and diseases, and provides an intuitive interface for linking compounds to their molecular functions and higher level biological effects.

Availability and implementation

http://conceptmetab.med.umich.edu

Contacts

akarnovsky@umich.edu or sartorma@umich.edu

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Cavalcante RG

PROVIDER: S-EPMC5860403 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Publications

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

Cavalcante Raymond G RG Patil Snehal S Weymouth Terry E TE Bendinskas Kestutis G KG Karnovsky Alla A Sartor Maureen A MA

Bioinformatics (Oxford, England) 20160121 10

<h4>Motivation</h4>Capabilities in the field of metabolomics have grown tremendously in recent years. Many existing resources contain the chemical properties and classifications of commonly identified metabolites. However, the annotation of small molecules (both endogenous and synthetic) to meaningful biological pathways and concepts still lags behind the analytical capabilities and the chemistry-based annotations. Furthermore, no tools are available to visually explore relationships and network ...[more]

PMID: 26794319

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Dataset Information

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

Motivation

Results

Availability and implementation

Contacts

Supplementary information

Publications

ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts.

Similar Datasets

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