Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data

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概要

• 論文の詳細を見る

• 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.

著者

• AMANO KOU

  School of Library and Information Science, University of Tsukuba

• ICHIKAWA HIROAKI

  National Institute of Agrobiological Sciences

• NAKAMURA HIDEMITSU

  National Institute of Agrobiological Sciences

• NUMA HISATAKA

  National Institute of Agrobiological Sciences

• FUKAMI-KOBAYASHI KAORU

  School of Library and Information Science, University of Tsukuba

• Amano Kou

  School Of Library And Information Science University Of Tsukuba:national Institute Of Agrobiological

• Onodera Natsuo

  School Of Library And Information Science University Of Tsukuba

• Nagamura Yoshiaki

  National Institute Of Agrobiological Resources

• Fukami-kobayashi Kaoru

  School Of Library And Information Science University Of Tsukuba:riken Bioresource Center

関連論文

• Self-organizing Clustering : Non-hierarchical Clustering for Large Scale DNA Sequence Data(Database/Software Paper)
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• Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data
• Self-organizing Clustering: Non-hierarchical Clustering for Large Scale DNA Sequence Data

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