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  • 标题:Improvement in Estimation of Unidentified Value (Gene Expression Data) in Biotechnology
  • 本地全文:下载
  • 作者:Baitali Nath ; Bindu Agarwalla ; Laxman Sahoo
  • 期刊名称:International Journal of Computer Science and Information Technologies
  • 电子版ISSN:0975-9646
  • 出版年度:2016
  • 卷号:7
  • 期号:2
  • 页码:1011-1013
  • 出版社:TechScience Publications
  • 摘要:In this era, DNA microarray technology is usedcombining with different data mining processes for extractingrelevant knowledge from genes of organisms to discover theassociation between noble diseases and their correlated genes.However, this gene expression data frequently contains absentvalues which are to be dealt with to stop them from causingdrastic affect in further analysis processes. To overcome the same,a number of missing-value recovery approaches are beingintroduced to serve the purpose. In this paper, a ClusteringApproach of Collaborative Filtering is projected to estimatemissing values more precisely than done by existing approaches.The Collaborative Filtering used in the process, which isprimarily used in Recommender Systems, has been united with abasic clustering method based on Rough-Set Theory to impute amissing value.
  • 关键词:Collaborative filtering; Clustering method; Gene;expression data; missing values; imputation.
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