Sequential pattern mining for protein function prediction

Miao Wang, Xue Qun Shang, Zhan Huai Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

The prediction of protein sequence function is one of the problems arising in the recent progress in bioinformatics. Traditional methods have its limits. We present a novel method of protein sequence function prediction based on sequential pattern mining. First, we use our designed sequential pattern mining algorithms to mine known function sequence dataset. Then, we build a classifier using the patterns generated to predict function of protein sequences. Experiments confirm the effectiveness of our method.

Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications - 4th International Conference, ADMA 2008, Proceedings
PublisherSpringer Verlag
Pages652-658
Number of pages7
ISBN (Print)3540881913, 9783540881919
DOIs
StatePublished - 2008
Event4th International Conference on Advanced Data Mining and Applications, ADMA 2008 - Chengdu, China
Duration: 8 Oct 200810 Oct 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5139 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Advanced Data Mining and Applications, ADMA 2008
Country/TerritoryChina
CityChengdu
Period8/10/0810/10/08

Keywords

  • Frequent closed pattern
  • Frequent pattern classifier
  • Frequent pattern mining
  • Protein function prediction

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