Protein sequence pattern mining with constraints

• Type: Article in International Scientific Journal
• Date: 2005

Authors

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

Indexing

ISI Web of Knowledge - 17 Citations

Scopus - 31 Citations

Scientific classification

CORDIS: Physical sciences > Computer science > Informatics

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-000-65V

DOI: 10.1007/11564126_14

Abstract (EN): Considering the characteristics of biological sequence databases, which typically have a small alphabet, a very long length and a relative small size (several hundreds of sequences), we propose a new sequence mining algorithm (gIL). gIL was developed for linear sequence pattern mining and results from the combination of some of the most efficient techniques used in sequence and itemset mining. The algorithm exhibits a high adaptability, yielding a smooth and direct introduction of various types of features into the mining process, namely the extraction of rigid and arbitrary gap patterns. Both breadth or a depth first traversal are possible. The experimental evaluation, in synthetic and real life protein databases, has shown that our algorithm has superior performance to state-of-the art algorithms. The use of constraints has also proved to be a very useful tool to specify user interesting patterns.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12