Bell, J. and Vigila, S. (2020) Gene Expression Analysis to Mine Highly Relevant Gene Data in Chronic Diseases and Annotating its GO Terms. EAI Endorsed Transactions on Energy Web.
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Abstract
Gene Expression Analysis seeks to find the highly expressive genes from a highly dimensional Microarray disease gene Database by using some statistical gene selection approaches based on supervised or unsupervised learning. Gene Ontology (GO) introduces a series of method for annotating gene functio
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 13:44 |
| Last Modified: | 11 Apr 2026 22:14 |
| URI: | http://eprints.eai.eu/id/eprint/31328 |
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