Evaluating the Significance of Sequence Motifs by the Minimum Description Length Principle

Document Type

Conference Proceeding

Publication Date

12-1-2000

Abstract

Sdiscover is a tool capable of finding subsequences, possibly separated by arbitrarily long gaps, in a set of sequences. These subsequences are referred to as motifs. This paper proposes a method to evaluate the significance of the sequence motifs found by Sdiscover. The method is based on the minimum description length principle and Shannon's coding theory. The equivalence of the proposed method to the Bayesian inference is also discussed.

Identifier

1642283251 (Scopus)

ISBN

[0964345692, 9780964345690]

Publication Title

Proceedings of the Joint Conference on Information Sciences

First Page

798

Last Page

801

Issue

2

Volume

5

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