Gene Expression Analysis to Mine Highly Relevant Gene Data in Chronic Diseases and Annotating its GO Terms

Gene Expression Analysis to Mine Highly Relevant Gene Data in Chronic Diseases and Annotating its GO Terms

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...

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Bibliographic Details
Main Authors: J. Bell, S. Vigila
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2020-11-01
Series:EAI Endorsed Transactions on Energy Web
Subjects:
gene expression analysis
chronic disorder
data mining
micro array
gene ontology
Online Access:https://eudl.eu/pdf/10.4108/eai.13-7-2018.164821

Internet

https://eudl.eu/pdf/10.4108/eai.13-7-2018.164821

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