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  • 标题:Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data
  • 本地全文:下载
  • 作者:Kou Amano ; Hiroaki Ichikawa ; Hidemitsu Nakamura
  • 期刊名称:Information and Media Technologies
  • 电子版ISSN:1881-0896
  • 出版年度:2007
  • 卷号:2
  • 期号:2
  • 页码:523-527
  • DOI:10.11185/imt.2.523
  • 出版社:Information and Media Technologies Editorial Board
  • 摘要:Recently, clustering has been recognized as an important and fundamental method that analyzes and classifies large-scale sequence data to provide useful information. We developed a novel clustering method designated as Self-organizing clustering (SOC) that uses oligonucleotide frequencies for large-scale DNA sequence data. We implemented SOC as a command-line program package, and developed a server that provides access to it enabling visualization of the results.SOC effectively and quickly classifies many sequences that have low or no homology to each other. The command-line program is downloadable at http://rgp.nias.affrc.go.jp/programs/. The on-line web site is publicly accessible at http://rgp.nias.affrc.go.jp/SOC/. The common gateway interface (CGI) for the server is also provided within the package.
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