Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Gene selection in time-series gene expression data
KTH, Skolan för datavetenskap och kommunikation (CSC), Beräkningsbiologi, CB.
2011 (Engelska)Ingår i: 6th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2011, 2011, s. 145-156Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

The dimensionality of biological data is often very high. Feature selection can be used to tackle the problem of high dimensionality. However, majority of the work in feature selection consists of supervised feature selection methods which require class labels. The problem further escalates when the data is time-series gene expression measurements that measure the effect of external stimuli on biological system. In this paper we propose an unsupervised method for gene selection from time-series gene expression data founded on statistical significance testing and swap randomization. We perform experiments with a publicly available mouse gene expression dataset and also a human gene expression dataset describing the exposure to asbestos. The results in both datasets show a considerable decrease in number of genes.

Ort, förlag, år, upplaga, sidor
2011. s. 145-156
Serie
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743
Nyckelord [en]
Feature Selection, Randomization, Statistical Significance, Time-series, Biological data, Class labels, Data sets, Expression measurements, External stimulus, Feature selection methods, Gene selection, High dimensionality, Time-series gene expression data, Unsupervised method, Bioinformatics, Feature extraction, Mammals, Gene expression
Nationell ämneskategori
Bioinformatik och systembiologi
Identifikatorer
URN: urn:nbn:se:kth:diva-150681DOI: 10.1007/978-3-642-24855-9_13ISI: 000308508800013Scopus ID: 2-s2.0-80455140577ISBN: 9783642248542 (tryckt)OAI: oai:DiVA.org:kth-150681DiVA, id: diva2:744920
Konferens
2-4 November 2011, Delft, Netherlands
Anmärkning

QC 20140909

Tillgänglig från: 2014-09-09 Skapad: 2014-09-08 Senast uppdaterad: 2017-03-24Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextScopus

Sök vidare i DiVA

Av författaren/redaktören
Meng, Chen
Av organisationen
Beräkningsbiologi, CB
Bioinformatik och systembiologi

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetricpoäng

doi
isbn
urn-nbn
Totalt: 872 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf