Deterministic pattern mining on genetic sequences

• Type: Chapter or Part of a Book
• Date: 2009

Authors

Ferreira, PG (Author) Other; Azevedo, PJ (Author) Other

Book

Title: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques

Pages: 277-301

ISBN: 9781605667669

Electronic ISBN: 9781605667676

Indexing

Scopus - 0 Citations

Scientific classification

CORDIS: Physical sciences > Computer science > Informatics > Applied informatics

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-009-CEH

DOI: 10.4018/978-1-60566-766-9.ch013

Abstract (EN): The recent increase in the number of complete genetic sequences freely available through specialized Internet databases presents big challenges for the research community. One such challenge is the efficient and effective search of sequence patterns, also known as motifs, among a set of related genetic sequences. Such patterns describe regions that may provide important insights about the structural and functional role of DNA and proteins. Two main classes can be considered: probabilistic patterns represent a model that simulates the sequences or part of the sequences under consideration and deterministic patterns that either match or not the input sequences. In this chapter a general overview of deterministic sequence mining over sets of genetic sequences is proposed. The authors formulate an architecture that divides the mining process workflow into a set of blocks. Each of these blocks is discussed individually. © 2010, IGI Global.

Language: English

Type (Professor's evaluation): Scientific