Prediction of Protein-Protein Interaction Strength Using Domain Features with Supervised Regression
抄録
Proteins in living organisms express various important functions by interacting with other proteins and molecules. Therefore, many efforts have been made to investigate and predict protein-protein interactions (PPIs). Analysis of strengths of PPIs is also important because such strengths are involved in functionality of proteins. In this paper, we propose several feature space mappings from protein pairs using protein domain information to predict strengths of PPIs. Moreover, we perform computational experiments employing two machine learning methods, support vector regression (SVR) and relevance vector machine (RVM), for dataset obtained from biological experiments. The prediction results showed that both SVR and RVM with our proposed features outperformed the best existing method.
収録刊行物
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- The Scientific World Journal
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The Scientific World Journal 2014 1-7, 2014-06-24
Hindawi Publishing Corporation
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キーワード
詳細情報 詳細情報について
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- CRID
- 1050564285747805440
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- NII論文ID
- 120005462601
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- ISSN
- 1537744X
- 23566140
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- HANDLE
- 2433/189275
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- 本文言語コード
- en
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- 資料種別
- journal article
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- データソース種別
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- IRDB
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- CiNii Articles
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