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ModeScore: A Method to Infer Changed Activity of Metabolic Function from Transcript Profiles Hoppe, Andreas Holzhütter, Hermann-Georg Metabolic network expression profile metabolic function 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Andreas Hoppe and Hermann-Georg Holzhütter 2012 Is Part Of OASIcs, Volume 26, German Conference on Bioinformatics 2012 InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.GCB.2012.1 urn:nbn:de:0030-drops-37134 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.GCB.2012.1 eng https://creativecommons.org/licenses/by-nd/3.0/legalcode