PFP: a computational framework for phylogenetic footprinting in prokaryotic genomes

Authors:
Dongsheng Che;Guojun Li;Shane T. Jensen;Jun S. Liu;Ying Xu
Affiliations:
Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA and Department of Computer Science, Un ...;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA;Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA;Department of Statistics, Harvard University, Cambridge, MA;Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA
Venue:
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Year:
2008

Citing 7
Cited 0

LEDA: a platform for combinatorial and geometric computing

LEDA: a platform for combinatorial and geometric computing
Accurate Prediction of Orthologous Gene Groups in Microbes

CSB '05 Proceedings of the 2005 IEEE Computational Systems Bioinformatics Conference
BioOptimizer: a Bayesian scoring function approach to motif discovery

Bioinformatics
Operon prediction without a training set

Bioinformatics
BEST: Binding-site Estimation Suite of Tools

Bioinformatics
Virtual Footprint and PRODORIC: an integrative framework for regulon prediction in prokaryotes

Bioinformatics
Combining phylogenetic motif discovery and motif clustering to predict co-regulated genes

Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Phylogenetic footprinting is a widely used approach for theprediction of transcription factor binding sites (TFBSs) through identificationof conserved motifs in the upstream sequences of orthologousgenes in eukaryotic genomes. However, this popular strategy may notbe directly applicable to prokaryotic genomes, where typically abouthalf of the genes in a genome form multiple-gene transcription unitsor operons. The promoter sequences for these operons are located in theinter-operonic rather than inter-genic regions, which require prediction ofTFBSs at the transcriptional unit instead of individual gene level. Wehave formulated as a bipartite graph matching problem the identificationof conserved operons (including both single-gene and multi-gene operons)whose individual gene members are orthologous between two genomesand present a graph-theoretic solution. By applying this method to Escherichiacoli K12 and 11 of its phylogeneticly neighboring species, wehave predicted 2, 478 sets of conserved operons, and discovered potentialbinding motifs for each of these operons. By comparing the predictionresults of our approach and other prediction approaches, we concludethat it is advantageous to use our approach for prediction of cis regulatorybinding sites in prokaryotes. The prediction software package PFPis available at http://csbl.bmb.uga.edu/~dongsheng/PFP.