Inferring gene correlation networks from transcription factor binding sites

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  • Mahdevar Ghasem
    Department of Bioinformatics, Institute of Biochemistry and Biophysics, University of Tehran
  • Nowzari-Dalini Abbas
    Department of Computer Science, School of Mathematics, Statistics, and Computer Science, University of Tehran
  • Sadeghi Mehdi
    National Institute of Genetic Engineering and Biotechnology School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM)

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Gene expression is a highly regulated biological process that is fundamental to the existence of phenotypes of any living organism. The regulatory relations are usually modeled as a network; simply, every gene is modeled as a node and relations are shown as edges between two related genes. This paper presents a novel method for inferring correlation networks, networks constructed by connecting co-expressed genes, through predicting co-expression level from genes promoter’s sequences. According to the results, this method works well on biological data and its outcome is comparable to the methods that use microarray as input. The method is written in C++ language and is available upon request from the corresponding author.

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