DocumentCode :
2301563
Title :
Computational inference of transcription factor cooperation by fuzzy frequent itemset mining
Author :
Lopez, F. Javier ; Cano, Carlos ; Garcia, Fernando ; Blanco, Alberto
Author_Institution :
Dept. of Comput. Sci. & Artificial Intell., Univ. of Granada, Granada, Spain
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
8
Abstract :
Eucaryotic gene control regions consist 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 (TF binding sites, TFBSs) and produce the correct gene expression patterns. We present a novel fuzzy approach to study significant co-occurences of closely located TFBSs in the yeast whole-genome. Our approach takes advantage of the ability of fuzzy techniques to handle imprecision, inherent to regulatory-regions location data. The methodology is based on a fuzzy frequent itemset mining algorithm and overcomes some of the limitations of previous approaches. The results obtained from the yeast genome allow us to propose the application of the procedure over more complex genomes in future works.
Keywords :
biology computing; data mining; fuzzy reasoning; genetics; computational inference; eucaryotic gene control regions; fuzzy frequent itemset mining; fuzzy techniques; gene expression patterns; regulatory DNA sequences; transcription factor cooperation; transcription factors; yeast whole-genome; Bioinformatics; DNA; Data mining; Genomics; Itemsets; Proteins;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5583991
Filename :
5583991
Link To Document :
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