Unsupervised dense regions discovery in DNA microarray data

Andy M. Yip, Edmond H. Wu, Michael K. Ng, Tony F. Chan

Research output: Chapter in book/report/conference proceedingChapterpeer-review

Abstract

In this paper, we introduce the notion of dense regions in DNA microarray data and present algorithms for discovering them. We demonstrate that dense regions are of statistical and biological significance through experiments. A dataset containing gene expression levels of 23 primate brain samples is employed to test our algorithms. Subsets of potential genes distinguishing between species and a subset of samples with potential abnormalities are identified.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning - IDEAL 2004
Subtitle of host publication5th International Conference, Exeter, UK, August 25-27, 2004, Proceedings
EditorsZheng Rong Yang, Richard Everson, Hujun Yin
PublisherSpringer Berlin Heidelberg
Pages71-77
Number of pages7
Edition1st
ISBN (Electronic)9783540286516
ISBN (Print)9783540228813
DOIs
Publication statusPublished - 13 Aug 2004
Event5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004 - Exeter, United Kingdom
Duration: 25 Aug 200427 Aug 2004
https://link.springer.com/book/10.1007/b99975

Publication series

NameLecture Notes in Computer Science
Volume3177
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameIDEAL: International Conference on Intelligent Data Engineering and Automated Learning

Conference

Conference5th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2004
Abbreviated titleIDEAL 2004
Country/TerritoryUnited Kingdom
CityExeter
Period25/08/0427/08/04
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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