TICL - A web tool for network-based interpretation of compound lists inferred by high-throughput metabolomics

Alexey V. Antonov, Sabine Dietmann, Philip Wong, Hans W. Mewes

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

High-throughput metabolomics is a dynamically developing technology that enables the mass separation of complex mixtures at very high resolution. Metabolic profiling has begun to be widely used in clinical research to study the molecular mechanisms of complex cell disorders. Similar to transcriptomics, which is capable of detecting genes at differential states, metabolomics is able to deliver a list of compounds differentially present between explored cell physiological conditions. The bioinformatics challenge lies in a statistically valid interpretation of the functional context for identified sets of metabolites. Here, we present TICL, a web tool for the automatic interpretation of lists of compounds. The major advance of TICL is that it not only provides a model of possible compound transformations related to the input list, but also implements a robust statistical framework to estimate the significance of the inferred model. The TICL web tool is freely accessible at http://mips.helmholtz- muenchen.de/proj/cmp.

Original languageEnglish
Pages (from-to)2084-2094
Number of pages11
JournalFEBS Journal
Volume276
Issue number7
DOIs
StatePublished - Apr 2009

Keywords

  • Bioinformatics tools for high-throughput metabolomics
  • Metabolomics
  • Statistical analysis and data mining
  • Statistical and bioinformatics tools
  • Web tools for metabolomics

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