title: Promoter prediction analysis on the whole human genome.
abstract: Promoter prediction programs (PPPs) are important for in silico gene discovery without support from expressed sequence tag (EST)/cDNA/mRNA sequences, in the analysis of gene regulation and in genome annotation. Contrary to previous expectations, a comprehensive analysis of PPPs reveals that no program simultaneously achieves sensitivity and a positive predictive value >65%. PPP performances deduced from a limited number of chromosomes or smaller data sets do not hold when evaluated at the level of the whole genome, with serious inaccuracy of predictions for non-CpG-island-related promoters. Some PPPs even perform worse than, or close to, pure random guessing.
authors.affiliation: Institute for Infocomm Research, 21 Heng Mui Keng Terrace, 119613 Singapore. bajicv@i2r.a-star.edu.sg
authors.forename: Vladimir B
authors.initials: VB
authors.lastname: Bajic
authors.forename: Sin Lam
authors.initials: SL
authors.lastname: Tan
authors.forename: Yutaka
authors.initials: Y
authors.lastname: Suzuki
authors.forename: Sumio
authors.initials: S
authors.lastname: Sugano
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D018899:CpG Islands / Q000235:genetics; D015894:Genome, Human; D006801:Humans; D008969:Molecular Sequence Data; D011401:Promoter Regions, Genetic / Q000235:genetics*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software; D012986:Software Validation