Abstract
Construction of co-expression network and extraction of network modules have been an appealing area of bioinformatics research. In literature, most existing algorithms of gene co-expression network extract network modules where all samples are considered. In this paper, we propose a method to construct a co-expression network based on mutual information and to extract network modules defined over a subset of samples. The method was applied over several real life gene expression datasets and the results are validated in terms of p value, Q value and topological properties.
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Mahanta, P., Bhattacharyya, D.K., Ghosh, A. (2013). A Subspace Module Extraction Technique for Gene Expression Data. In: Maji, P., Ghosh, A., Murty, M.N., Ghosh, K., Pal, S.K. (eds) Pattern Recognition and Machine Intelligence. PReMI 2013. Lecture Notes in Computer Science, vol 8251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45062-4_89
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DOI: https://doi.org/10.1007/978-3-642-45062-4_89
Publisher Name: Springer, Berlin, Heidelberg
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