title: Finding short DNA motifs using permuted Markov models.
abstract: Many short DNA motifs, such as transcription factor binding sites (TFBS) and splice sites, exhibit strong local as well as nonlocal dependence. We introduce permuted variable length Markov models (PVLMM) which could capture the potentially important dependencies among positions and apply them to the problem of detecting splice and TFB sites. They have been satisfactory from the viewpoint of prediction performance and also give ready biological interpretations of the sequence dependence observed. The issue of model selection is also studied.
authors.affiliation: Department of Statistics, University of California- Berkeley, 367 Evans Hall, Berkeley CA 94720-3860, USA. xiaoyue@stat.berkeley.edu
authors.forename: Xiaoyue
authors.initials: X
authors.lastname: Zhao
authors.forename: Haiyan
authors.initials: H
authors.lastname: Huang
authors.forename: Terence P
authors.initials: TP
authors.lastname: Speed
mesh_terms: D000465:Algorithms; D001665:Binding Sites; D019295:Computational Biology; D004247:DNA / Q000235:genetics* / Q000378:metabolism; D008390:Markov Chains; D015233:Models, Statistical; D011401:Promoter Regions, Genetic / Q000235:genetics*; D011485:Protein Binding; D014157:Transcription Factors / Q000235:genetics* / Q000378:metabolism
chemical_list: D014157:Transcription Factors; D004247:DNA