ConceptMetab: exploring relationships among metabolite sets to identify links among biomedical concepts
Author(s) -
Raymond G. Cavalcante,
Snehal Patil,
Terry E. Weymouth,
Kestutis Bendinskas,
Alla Karnovsky,
Maureen A. Sartor
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw016
Subject(s) - metabolite , computer science , computational biology , data science , biology , biochemistry
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.
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