License: Creative Commons Attribution-NoDerivs 3.0 Unported license (CC BY-ND 3.0)
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DOI: 10.4230/OASIcs.GCB.2012.1
URN: urn:nbn:de:0030-drops-37134
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Hoppe, Andreas ; Holzhütter, Hermann-Georg

ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles

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Genome-wide transcript profiles are often the only available quantitative data for a particular perturbation of a cellular system and their interpretation with respect to the metabolism is a major challenge in systems biology, especially beyond on/off distinction of genes.

We present a method that predicts activity changes of metabolic functions by scoring reference flux distributions based on relative transcript profiles, providing a ranked list of most regulated functions. Then, for each metabolic function, the involved genes are ranked upon how much they represent a specific regulation pattern. Compared with the naïve pathway-based approach, the reference modes can be chosen freely, and they represent full metabolic functions, thus, directly provide testable hypotheses for the metabolic study.

In conclusion, the novel method provides promising functions for subsequent experimental elucidation together with outstanding associated genes, solely based on transcript profiles.

BibTeX - Entry

  author =	{Andreas Hoppe and Hermann-Georg Holzh{\"u}tter},
  title =	{{ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles}},
  booktitle =	{German Conference on Bioinformatics 2012},
  pages =	{1--11},
  series =	{OpenAccess Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-44-6},
  ISSN =	{2190-6807},
  year =	{2012},
  volume =	{26},
  editor =	{Sebastian B{\"o}cker and Franziska Hufsky and Kerstin Scheubert and Jana Schleicher and Stefan Schuster},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-37134},
  doi =		{10.4230/OASIcs.GCB.2012.1},
  annote =	{Keywords: Metabolic network, expression profile, metabolic function}

Keywords: Metabolic network, expression profile, metabolic function
Collection: German Conference on Bioinformatics 2012
Issue Date: 2012
Date of publication: 13.09.2012

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