Title: More robust detection of motifs in coexpressed genes by using phylogenetic information
Authors: Monsieurs, Pieter ×
Thijs, Gert
Fadda, Abeer
De Keersmaecker, Sigrid
Vanderleyden, Jozef
De Moor, Bart
Marchal, Kathleen #
Issue Date: Mar-2006
Publisher: BioMed Central
Series Title: BMC Bioinformatics vol:7 issue:1 pages:160
Abstract: AB - ABSTRACT: BACKGROUND: Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of genes containing the motif versus the number lacking the motif might not be sufficiently high to allow detection by classical motif detection tools. To still recover motifs which are not significantly enriched but still present, we developed a procedure in which we use phylogenetic footprinting to first delineate all potential motifs in each gene. Then we mutually compare all detected motifs and identify the ones that are shared by at least a few genes in the data set as potential candidates. RESULTS: We applied our methodology to a compiled test data set containing known regulatory motifs and to two biological data sets derived from genome wide expression studies. By executing four consecutive steps of 1) identifying conserved regions in orthologous intergenic regions, 2) aligning these conserved regions, 3) clustering the conserved regions containing similar regulatory regions followed by extraction of the regulatory motifs and 4) screening the input intergenic sequences with detected regulatory motif models, our methodology proves to be a powerful tool for detecting regulatory motifs when a low signal to noise ratio is present in the input data set. Comparing our results with two other motif detection algorithms points out the robustness of our algorithm. CONCLUSIONS: We developed an approach that can reliably identify multiple regulatory motifs lacking a high degree of overrepresentation in a set of coexpressed genes (motifs belonging to sparsely connected hubs in the regulatory network) by exploiting the advantages of using both coexpression and phylogenetic information
ISSN: 1471-2105
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - STADIUS, Stadius Centre for Dynamical Systems, Signal Processing and Data Analytics
Centre of Microbial and Plant Genetics
Electrical Engineering - miscellaneous
× corresponding author
# (joint) last author

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