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hmm2_modeling_dna_heterogeneities
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HMM2 modeling for detection of intergenic heterogeneities in bacterial genomes
Catherine Eng1,2, Charu Gaur-Asthana1, Bertrand Aigle2, Sebastien Hergalant1, Jean-Francois Mari1* and Pierre Leblond2*
1LORIA, UMR CNRS 7503 INRIA Lorraine, Campus scientifique, BP 239, 54506 Vandoeuvre-les-Nancy, France.
2Laboratoire de Genetique et Microbiologie UMR UHP-INRA 1128, IFR 110, Nancy Universite, Faculte des Sciences et Techniques, BP 239, 54506 Vandoeuvre-les-Nancy, France
Additional data (in reference to the article - Submitted to Bioinformatics)
HMM2 model generation
Parameter testing
i. set-sco (test dataset) - analysis of sigma factor SigR regulonSii results for dagA Analysis
Genome Analysis
Analysis of Streptomyces coelicolor A3(2) genome (sigma factor SigR results)Peak_Extraction on whole genome
16,913 iPeaks motifs ( DNA sequence underlying iPeaks )TFBS Data Mining results
Clustering (ClusterMean Algorithm)
iPeaks clustered into 360 clusters. For each cluster consensus was generated by Multalin program and the statistical significance validated by R'MES program. Result: 357 consensuses
Modeling TFBS consensuses
TFBS proposed consensuses motifs
Pattern Recognition for Bioinformatics, Nice, June 17-19, 2013 & Computational Intelligence Methods for Bioinformatics and Biostatistics, Nice, June 20-22, 2013