title: Predicting sigma28 promoters in eleven Shewanella genomes.
abstract: An iterative position-specific score matrix (PSSM)-based approach was used to predict sigma(28) promoters in 11 Shewanella genomes. The Shewanella Correlation Browser was used to distinguish true-positive predictions from false-positive predictions in Shewanella oneidensis MR-1 by generating a sigma(28)-regulated transcriptional network from transcriptional profiling data. This dual-pronged approach identified several genes that have sigma(28) promoters and that may be involved with motility or chemotaxis in Shewanella.
authors.affiliation: Department of Geography and Environmental Engineering, The Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD, USA.
authors.forename: Wenjie
authors.initials: W
authors.lastname: Song
authors.forename: Frank S
authors.initials: FS
authors.lastname: Juhn
authors.forename: Daniel Q
authors.initials: DQ
authors.lastname: Naiman
authors.forename: Konstantinos T
authors.initials: KT
authors.lastname: Konstantinidis
authors.forename: Timothy S
authors.initials: TS
authors.lastname: Gardner
authors.forename: Mandy J
authors.initials: MJ
authors.lastname: Ward
mesh_terms: D000465:Algorithms; D001426:Bacterial Proteins / Q000378:metabolism*; D001665:Binding Sites; D019295:Computational Biology; D016680:Genome, Bacterial; D011401:Promoter Regions, Genetic; D020592:Shewanella / Q000235:genetics*; D012808:Sigma Factor / Q000378:metabolism*
chemical_list: D001426:Bacterial Proteins; C064971:FliA protein, Bacteria; D012808:Sigma Factor