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http://nopr.niscpr.res.in/handle/123456789/7710Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Hsieh, K-L | - |
| dc.date.accessioned | 2010-03-30T07:04:13Z | - |
| dc.date.available | 2010-03-30T07:04:13Z | - |
| dc.date.issued | 2010-04 | - |
| dc.identifier.issn | 0975-1084 (Online); 0022-4456 (Print) | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/7710 | - |
| dc.description | 278-283 | en_US |
| dc.description.abstract | In this study, dimension reduction and clustering techniques are incorporated in an integrated soft computing approach to achieve classification of organism. It provides useful information about organisms classification based on codon usage. Finally, a case study was conducted to demonstrate rationality and feasibility of proposed approach. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | CSIR | en_US |
| dc.source | JSIR Vol.69(04) [April 2010] | en_US |
| dc.subject | Codon usage | en_US |
| dc.subject | Principle component analysis (PCA) | en_US |
| dc.subject | Self-organizing feature map (SOM) | en_US |
| dc.title | An integrated data mining approach based on PCA and SOM techniques to achieve organism classification | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | JSIR Vol.69(04) [April 2010] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| JSIR 69(4) 278-283.pdf | 69.68 kB | Adobe PDF | View/Open |
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