@inproceedings{7e2d2c644889460ca8bca75d28bb6a72,
title = "MISAE: A new approach for regulatory motif extraction",
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.",
author = "Zhaohui Sun and Jingyi Yang and Deogun, {Jitender S.}",
year = "2004",
language = "English (US)",
isbn = "0769521940",
series = "Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004",
publisher = "IEEE Computer Society",
pages = "173--181",
booktitle = "Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004",
note = "Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004 ; Conference date: 16-08-2004 Through 19-08-2004",
}