A Novel Algorithm for Coexpression Network Analysis and Its Application to Arabidopsis Genes
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- Ogata Yoshiyuki
- Kazusa DNA Research Institute
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- Sakurai Nozomu
- Kazusa DNA Research Institute
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- Aoki Koh
- Kazusa DNA Research Institute
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- Okazaki Koei
- Kazusa DNA Research Institute
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- Saito Kazuki
- Graduate School of Pharmaceutical Sciences, Chiba Univ.
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- Shibata Daisuke
- Kazusa DNA Research Institute
Bibliographic Information
- Other Title
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- 共発現ネットワーク解析アルゴリズムの構築とシロイヌナズナ遺伝子への適用
Description
Gene coexpression analysis that depicts gene-to-gene correlations became prevalent in plant transcriptome research. Methods of network analysis have been developed to detect connected groups of genes from a large network. However, within the group, it was difficult to exclude the possibility that the group was also highly connected with genes on the outside of the group. To extract genes with dense within-group connectivity and sparse outside connectivity, we developed a novel algorithm by introducing quantitative index "network specificity". To identify genes specifically coexpressed with a query gene, the first procedure was to extract a group of genes that have high network specificity to a query gene. The second procedure was to calculate network specificity of the group to estimate within-group coexpression quantitatively. By applying this algorithm to genome-wide analysis of Arabidopsis gene coexpression, we identified a number of coexpression groups.
Journal
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- Plant and Cell Physiology Supplement
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Plant and Cell Physiology Supplement 2007 (0), 433-433, 2007
The Japanese Society of Plant Physiologists
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Details 詳細情報について
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- CRID
- 1390282680608294784
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- NII Article ID
- 130006992860
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed