MetaboSignal: a network-based approach for topological analysis of metabotype regulation via metabolic and signaling pathways

Andrea Rodriguez-Martinez; Rafael Ayala; Joram M Posma; Ana L Neves; Dominique Gauguier; Jeremy K Nicholson; Marc-Emmanuel Dumas

doi:10.1093/bioinformatics/btw697

MetaboSignal: a network-based approach for topological analysis of metabotype regulation via metabolic and signaling pathways

Bioinformatics. 2017 Mar 1;33(5):773-775. doi: 10.1093/bioinformatics/btw697.

Authors

Andrea Rodriguez-Martinez¹, Rafael Ayala¹, Joram M Posma¹, Ana L Neves¹, Dominique Gauguier^{1

2}, Jeremy K Nicholson¹, Marc-Emmanuel Dumas¹

Affiliations

¹ Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, SW7 2AZ London, UK.
² Sorbonne Universities, University Pierre & Marie Curie, University Paris Descartes, Sorbonne Paris Cité, INSERMUMR_S 1138, Cordeliers Research Centre, 75006 Paris, France.

Abstract

Summary: MetaboSignal is an R package that allows merging metabolic and signaling pathways reported in the Kyoto Encyclopaedia of Genes and Genomes (KEGG). It is a network-based approach designed to navigate through topological relationships between genes (signaling- or metabolic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape of metabolic phenotypes.

Availability and implementation: MetaboSignal is available from Bioconductor: https://bioconductor.org/packages/MetaboSignal/.

Contact: m.dumas@imperial.ac.uk .

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Adipose Tissue / metabolism
Animals
Computational Biology / methods*
Metabolic Networks and Pathways*
Quantitative Trait Loci
Rats
Signal Transduction*
Software*

Grants and funding

MR/K501281/1/Medical Research Council/United Kingdom