| Download | - View accepted manuscript: Mining biological information from 3D gene expression data : the OPTricluster algorithm (PDF, 769 KiB)
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| DOI | Resolve DOI: https://doi.org/10.1186/1471-2105-13-54 |
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| Author | Search for: Tchagang, Alain B.1; Search for: Phan, Sieu1; Search for: Famili, Fazel1; Search for: Shearer, Heather2; Search for: Fobert, Pierre2; Search for: Huang, Yi2; Search for: Zou, Jitao2; Search for: Huang, Daiqing2; Search for: Cutler, Adrian2; Search for: Liu, Ziying1; Search for: Pan, Youlian1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
- National Research Council of Canada. NRC Plant Biotechnology Institute
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| Format | Text, Article |
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| Abstract | Background: Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. |
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| Publication date | 2012-04-04 |
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| In | |
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| Language | English |
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| Peer reviewed | Yes |
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| NPARC number | 20262885 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | 23c1f50e-c76a-4c55-9354-84e8181343f4 |
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| Record created | 2012-07-10 |
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| Record modified | 2020-04-21 |
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