Tissue Classification Using Gene Expression Data and Artificial Neural Network Ensembles
Identifieur interne : 000F65 ( Main/Exploration ); précédent : 000F64; suivant : 000F66Tissue Classification Using Gene Expression Data and Artificial Neural Network Ensembles
Auteurs : Huijuan Lu [République populaire de Chine] ; Jinxiang Zhang [République populaire de Chine, Niger] ; Lei Zhang [République populaire de Chine]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2006.
Abstract
Abstract: An important challenge in the use of large-scale gene expression data for biological classification occurs when the number of genes far exceeds the number of samples. This situation will make the classification results are unstable. Thus, a tissue classification method using artificial neural network ensembles was proposed. In this method, a feature preselection method is presented to identify significant genes highly correlated with tissue types. Then pseudo data sets for training the component neural network of ensembles were generated by bagging. The predictions of those individual networks were combined by simple averaging method. Some data experiments have shown that this classification method yields competitive results on several publicly available datasets.
Url:
DOI: 10.1007/11816102_85
Affiliations:
Links toward previous steps (curation, corpus...)
- to stream Istex, to step Corpus: 003401
- to stream Istex, to step Curation: 003146
- to stream Istex, to step Checkpoint: 000936
- to stream Main, to step Merge: 000F81
- to stream Main, to step Curation: 000F65
Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct:series"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Tissue Classification Using Gene Expression Data and Artificial Neural Network Ensembles</title><author><name sortKey="Lu, Huijuan" sort="Lu, Huijuan" uniqKey="Lu H" first="Huijuan" last="Lu">Huijuan Lu</name></author><author><name sortKey="Zhang, Jinxiang" sort="Zhang, Jinxiang" uniqKey="Zhang J" first="Jinxiang" last="Zhang">Jinxiang Zhang</name></author><author><name sortKey="Zhang, Lei" sort="Zhang, Lei" uniqKey="Zhang L" first="Lei" last="Zhang">Lei Zhang</name></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:1C5708A4B29FA51AF60972268F27362C4CB83218</idno><date when="2006" year="2006">2006</date><idno type="doi">10.1007/11816102_85</idno><idno type="url">https://api.istex.fr/document/1C5708A4B29FA51AF60972268F27362C4CB83218/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">003401</idno><idno type="wicri:Area/Istex/Curation">003146</idno><idno type="wicri:Area/Istex/Checkpoint">000936</idno><idno type="wicri:doubleKey">0302-9743:2006:Lu H:tissue:classification:using</idno><idno type="wicri:Area/Main/Merge">000F81</idno><idno type="wicri:Area/Main/Curation">000F65</idno><idno type="wicri:Area/Main/Exploration">000F65</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Tissue Classification Using Gene Expression Data and Artificial Neural Network Ensembles</title><author><name sortKey="Lu, Huijuan" sort="Lu, Huijuan" uniqKey="Lu H" first="Huijuan" last="Lu">Huijuan Lu</name><affiliation wicri:level="3"><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Computer Applications, China Jiliang University, 310018, Hangzhou</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation><affiliation wicri:level="4"><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Computer Science, Zhejiang University, 310027, Hangzhou</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName><orgName type="university">Université de Zhejiang</orgName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">République populaire de Chine</country></affiliation></author><author><name sortKey="Zhang, Jinxiang" sort="Zhang, Jinxiang" uniqKey="Zhang J" first="Jinxiang" last="Zhang">Jinxiang Zhang</name><affiliation wicri:level="3"><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Department of Computer Science, Zhejiang Education Institute, 310012, Hangzhou</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Niger</country></affiliation></author><author><name sortKey="Zhang, Lei" sort="Zhang, Lei" uniqKey="Zhang L" first="Lei" last="Zhang">Lei Zhang</name><affiliation wicri:level="3"><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Institute of Computer Applications, China Jiliang University, 310018, Hangzhou</wicri:regionArea><placeName><settlement type="city">Hangzhou</settlement><region type="province">Zhejiang</region></placeName></affiliation><affiliation><wicri:noCountry code="no comma">E-mail: leizhang4662@sina.com</wicri:noCountry></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2006</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">1C5708A4B29FA51AF60972268F27362C4CB83218</idno><idno type="DOI">10.1007/11816102_85</idno><idno type="ChapterID">85</idno><idno type="ChapterID">Chap85</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: An important challenge in the use of large-scale gene expression data for biological classification occurs when the number of genes far exceeds the number of samples. This situation will make the classification results are unstable. Thus, a tissue classification method using artificial neural network ensembles was proposed. In this method, a feature preselection method is presented to identify significant genes highly correlated with tissue types. Then pseudo data sets for training the component neural network of ensembles were generated by bagging. The predictions of those individual networks were combined by simple averaging method. Some data experiments have shown that this classification method yields competitive results on several publicly available datasets.</div></front></TEI><affiliations><list><country><li>Niger</li><li>République populaire de Chine</li></country><region><li>Zhejiang</li></region><settlement><li>Hangzhou</li></settlement><orgName><li>Université de Zhejiang</li></orgName></list><tree><country name="République populaire de Chine"><region name="Zhejiang"><name sortKey="Lu, Huijuan" sort="Lu, Huijuan" uniqKey="Lu H" first="Huijuan" last="Lu">Huijuan Lu</name></region><name sortKey="Lu, Huijuan" sort="Lu, Huijuan" uniqKey="Lu H" first="Huijuan" last="Lu">Huijuan Lu</name><name sortKey="Lu, Huijuan" sort="Lu, Huijuan" uniqKey="Lu H" first="Huijuan" last="Lu">Huijuan Lu</name><name sortKey="Zhang, Jinxiang" sort="Zhang, Jinxiang" uniqKey="Zhang J" first="Jinxiang" last="Zhang">Jinxiang Zhang</name><name sortKey="Zhang, Lei" sort="Zhang, Lei" uniqKey="Zhang L" first="Lei" last="Zhang">Lei Zhang</name></country><country name="Niger"><noRegion><name sortKey="Zhang, Jinxiang" sort="Zhang, Jinxiang" uniqKey="Zhang J" first="Jinxiang" last="Zhang">Jinxiang Zhang</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/OcrV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000F65 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000F65 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= OcrV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= ISTEX:1C5708A4B29FA51AF60972268F27362C4CB83218
|texte= Tissue Classification Using Gene Expression Data and Artificial Neural Network Ensembles
}}
| This area was generated with Dilib version V0.6.32. |  |