Literature DB >> 9322017

Data mining for regulatory elements in yeast genome.

A Brazma1, J Vilo, E Ukkonen, K Valtonen.   

Abstract

We have examined methods and developed a general software tool for finding and analyzing combinations of transcription factor binding sites that occur relatively often in gene upstream regions (putative promoter regions) in the yeast genome. Such frequently occurring combinations may be essential parts of possible promoter classes. The regions upstream to all genes were first isolated from the yeast genome database MIPS using the information in the annotation files of the database. The ones that do not overlap with coding regions were chosen for further studies. Next, all occurrences of the yeast transcription factor binding sites, as given in the IMD database, were located in the genome and in the selected regions in particular. Finally, by using a general purpose data mining software in combination with our own software, which parametrizes the search, we can find the combinations of binding sites that occur in the upstream regions more frequently than would be expected on the basis of the frequency of individual sites. The procedure also finds so-called association rules present in such combinations. The developed tool is available for use through the WWW.

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Year:  1997        PMID: 9322017

Source DB:  PubMed          Journal:  Proc Int Conf Intell Syst Mol Biol        ISSN: 1553-0833


  8 in total

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2.  Recent computational approaches to understand gene regulation: mining gene regulation in silico.

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5.  Quantitative comparisons of in vitro assays for estrogenic activities.

Authors:  H Fang; W Tong; R Perkins; A M Soto; N V Prechtl; D M Sheehan
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6.  An algorithm for identifying novel targets of transcription factor families: application to hypoxia-inducible factor 1 targets.

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7.  Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining.

Authors:  Xochitl C Morgan; Shulin Ni; Daniel P Miranker; Vishwanath R Iyer
Journal:  BMC Bioinformatics       Date:  2007-11-15       Impact factor: 3.169

8.  Current approaches to gene regulatory network modelling.

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  8 in total

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