MISAE: A new approach for regulatory motif extraction

Zhaohui Sun, Jingyi Yang, Jitender S. Deogun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

The recognition of regulatory motifs of co-regulated genes is essential for understanding the regulatory mechanisms. However, the automatic extraction of regulatory motifs from a given data set of the upstream non-coding DNA sequences of a family of co-regulated genes is difficult because regulatory motifs are often subtle and inexact. This problem is further complicated by the corruption of the data sets. In this paper, a new approach called Mismatch-allowed Probabilistic Suffix Tree Motif Extraction (MISAE) is proposed. It combines the mismatch-allowed probabilistic suffix tree that is a probabilistic model and local prediction for the extraction of regulatory motifs. The proposed approach is tested on 15 co-regulated gene families and compares favorably with other state-of-the-art approaches. Moreover, MISAE performs well on "corrupted" data sets. It is able to extract the motif from a "corrupted" data set with less than one fourth of the sequences containing the real motif.

Original languageEnglish (US)
Title of host publicationProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
PublisherIEEE Computer Society
Pages173-181
Number of pages9
ISBN (Print)0769521940, 9780769521947
StatePublished - 2004
EventProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 - Stanford, CA, United States
Duration: Aug 16 2004Aug 19 2004

Publication series

NameProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Conference

ConferenceProceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004
CountryUnited States
CityStanford, CA
Period8/16/048/19/04

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Sun, Z., Yang, J., & Deogun, J. S. (2004). MISAE: A new approach for regulatory motif extraction. In Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 (pp. 173-181). (Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004). IEEE Computer Society.