Literature DB >> 19292876

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

Alexey V Antonov1, Sabine Dietmann, Philip Wong, Hans W Mewes.   

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.

Entities:  

Mesh:

Year:  2009        PMID: 19292876     DOI: 10.1111/j.1742-4658.2009.06943.x

Source DB:  PubMed          Journal:  FEBS J        ISSN: 1742-464X            Impact factor:   5.542


  15 in total

Review 1.  Extending biochemical databases by metabolomic surveys.

Authors:  Oliver Fiehn; Dinesh K Barupal; Tobias Kind
Journal:  J Biol Chem       Date:  2011-05-12       Impact factor: 5.157

2.  Pathway discovery in metabolic networks by subgraph extraction.

Authors:  Karoline Faust; Pierre Dupont; Jérôme Callut; Jacques van Helden
Journal:  Bioinformatics       Date:  2010-03-12       Impact factor: 6.937

3.  Use of reconstituted metabolic networks to assist in metabolomic data visualization and mining.

Authors:  Fabien Jourdan; Ludovic Cottret; Laurence Huc; David Wildridge; Richard Scheltema; Anne Hillenweck; Michael P Barrett; Daniel Zalko; David G Watson; Laurent Debrauwer
Journal:  Metabolomics       Date:  2010-01-06       Impact factor: 4.290

4.  The MetabolomeExpress Project: enabling web-based processing, analysis and transparent dissemination of GC/MS metabolomics datasets.

Authors:  Adam J Carroll; Murray R Badger; A Harvey Millar
Journal:  BMC Bioinformatics       Date:  2010-07-14       Impact factor: 3.169

5.  Pathos: a web facility that uses metabolic maps to display experimental changes in metabolites identified by mass spectrometry.

Authors:  David P Leader; Karl Burgess; Darren Creek; Michael P Barrett
Journal:  Rapid Commun Mass Spectrom       Date:  2011-11-30       Impact factor: 2.419

6.  MIPS: curated databases and comprehensive secondary data resources in 2010.

Authors:  H Werner Mewes; Andreas Ruepp; Fabian Theis; Thomas Rattei; Mathias Walter; Dmitrij Frishman; Karsten Suhre; Manuel Spannagl; Klaus F X Mayer; Volker Stümpflen; Alexey Antonov
Journal:  Nucleic Acids Res       Date:  2010-11-24       Impact factor: 16.971

7.  BioProfiling.de: analytical web portal for high-throughput cell biology.

Authors:  Alexey V Antonov
Journal:  Nucleic Acids Res       Date:  2011-05-23       Impact factor: 16.971

8.  Path finding methods accounting for stoichiometry in metabolic networks.

Authors:  Jon Pey; Joaquín Prada; John E Beasley; Francisco J Planes
Journal:  Genome Biol       Date:  2011-05-27       Impact factor: 13.583

9.  GeneSet2miRNA: finding the signature of cooperative miRNA activities in the gene lists.

Authors:  Alexey V Antonov; Sabine Dietmann; Philip Wong; Dominik Lutter; Hans W Mewes
Journal:  Nucleic Acids Res       Date:  2009-05-06       Impact factor: 16.971

Review 10.  Metabolomic fingerprinting: challenges and opportunities.

Authors:  Alyssa K Kosmides; Kubra Kamisoglu; Steve E Calvano; Siobhan A Corbett; Ioannis P Androulakis
Journal:  Crit Rev Biomed Eng       Date:  2013
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.