4.5 Article Proceedings Paper

Finding short DNA motifs using permuted Markov models

Journal

JOURNAL OF COMPUTATIONAL BIOLOGY
Volume 12, Issue 6, Pages 894-906

Publisher

MARY ANN LIEBERT, INC
DOI: 10.1089/cmb.2005.12.894

Keywords

permuted variable length Markov models; maximal dependence decomposition models; weight matrix models; model selection; DNA motifs

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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.

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