Abstract
Eucaryotic gene control regions consists of a promoter plus regulatory DNA sequences which may appear distant from the gene promoter. Regulatory proteins (called transcription factors, TFs), coordinately bind to these regions and produce the correct gene expression patterns. However, most of previous works which study regulatory modules limit their attention to gene promoters. Taking advantage of the ability of fuzzy techniques to handle imprecision, inherent to TFBSs and regulatory-regions location data, a novel fuzzy approach is developed in this work to study significant co-occurrences of closely located TFBSs in the yeast whole-genome. Hence, we firstly obtained fuzzy groups of closely-located TFBSs in the genome by using a clustering algorithm. Then, a fuzzy frequent itemset mining algorithm was applied over the set of fuzzy groups to get significant co-occurrences of TFs. An integrative analysis using STRING revealed a number of significant TF combinations, many of them agreeing with previously published knowledge.
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Lopez, F.J., Cano, C., Garcia, F., Blanco, A. (2009). A Fuzzy Approach for Studying Combinatorial Regulatory Actions of Transcription Factors in Yeast. In: Corchado, E., Yin, H. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2009. IDEAL 2009. Lecture Notes in Computer Science, vol 5788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04394-9_58
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DOI: https://doi.org/10.1007/978-3-642-04394-9_58
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