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Application of Regulatory Sequence Analysis and Metabolic Network Analysis to the Interpretation of Gene Expression Data

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Computational Biology (JOBIM 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2066))

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Abstract

We present two complementary approaches for the interpretation of clusters of co-regulated genes, such as those obtained from DNA chips and related methods. Starting from a cluster of genes with similar expression profiles, two basic questions can be asked:

  1. 1.

    Which mechanism is responsible for the coordinated transcriptional response of the genes? This question is approached by extracting motifs that are shared between the upstream sequences of these genes. The motifs extracted are putative cis-acting regulatory elements.

  2. 2.

    What is the physiological meaning for the cell to express together these genes? One way to answer the question is to search for potential metabolic pathways that could be catalyzed by the products of the genes. This can be done by selecting the genes from the cluster that code for enzymes, and trying to assemble the catalyzed reactions to form metabolic pathways.

We present tools to answer these two questions, and we illustrate their use with selected examples in the yeast Saccharomyces cerevisiae. The tools are available on the web (http://ucmb.ulb.ac.be/bioinformatics/rsa-tools/; http://www.ebi.ac.uk/research/pfbp/; http://www.soi.city.ac.uk/~msch/).

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van Helden, J., Gilbert, D., Wernisch, L., Schroeder, M., Wodak, S. (2001). Application of Regulatory Sequence Analysis and Metabolic Network Analysis to the Interpretation of Gene Expression Data. In: Gascuel, O., Sagot, MF. (eds) Computational Biology. JOBIM 2000. Lecture Notes in Computer Science, vol 2066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45727-5_13

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  • DOI: https://doi.org/10.1007/3-540-45727-5_13

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  • Print ISBN: 978-3-540-42242-6

  • Online ISBN: 978-3-540-45727-5

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