Protein interaction networks : computational analysis
著者
書誌事項
Protein interaction networks : computational analysis
Cambridge University Press, c2009
大学図書館所蔵 全6件
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  岩手
  宮城
  秋田
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  福島
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  東京
  神奈川
  新潟
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  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
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内容説明・目次
内容説明
The analysis of protein-protein interactions is fundamental to the understanding of cellular organization, processes, and functions. Proteins seldom act as single isolated species; rather, proteins involved in the same cellular processes often interact with each other. Functions of uncharacterized proteins can be predicted through comparison with the interactions of similar known proteins. Recent large-scale investigations of protein-protein interactions using such techniques as two-hybrid systems, mass spectrometry, and protein microarrays have enriched the available protein interaction data and facilitated the construction of integrated protein-protein interaction networks. The resulting large volume of protein-protein interaction data has posed a challenge to experimental investigation. This book provides a comprehensive understanding of the computational methods available for the analysis of protein-protein interaction networks. It offers an in-depth survey of a range of approaches, including statistical, topological, data-mining, and ontology-based methods. The author discusses the fundamental principles underlying each of these approaches and their respective benefits and drawbacks, and she offers suggestions for future research.
目次
- 1. Introduction
- 2. Experimental approaches to generation of protein-protein interaction data
- 3. Computational methods for the prediction of protein-protein interactions
- 4. Basic properties and measurements of protein interaction networks
- 5. Modularity analysis of protein interaction networks
- 6. Topological analysis of protein interaction networks Woo-chang Hwang
- 7. Distance-based modularity analysis
- 8. Graph-theoretic approaches to modularity analysis
- 9. Flow-based analysis of protein interaction networks
- 10. Statistics and machine learning based analysis of protein interaction networks Pritam Chanda and Lei Shi
- 11. Integration of gene ontology into the analysis of protein interaction networks Young-rae Cho
- 12. Data fusion in the analysis of protein interaction networks
- 13. Conclusion.
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