Predicting protein-protein interactions by weighted pseudo amino acid composition
| Autor: | Yunus Emre Göktepe, N.A. �°, lhan �°, N.A. lhan, Şirzat Kahramanlı |
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| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
business.industry Context (language use) Pattern recognition Computational biology Library and Information Sciences Biology General Biochemistry Genetics and Molecular Biology Protein–protein interaction Support vector machine 03 medical and health sciences 030104 developmental biology Order (biology) Feature (machine learning) Artificial intelligence Correlation factors Representation (mathematics) business Pseudo amino acid composition Information Systems |
| Zdroj: | International Journal of Data Mining and Bioinformatics. 15:272 |
| ISSN: | 1748-5681 1748-5673 |
| Popis: | Protein-protein interactions hold very important roles in biological processes. Prediction of PPIs is important for understanding these processes. In this context, substantive representations of proteins are needed during the process of interaction prediction in order to achieve higher prediction accuracy. In this paper, a new feature representation method, based on the concept of Chou's pseudo amino acid composition, was introduced. It is composed of the weighted amino acid composition information and the correlation factors of the protein. Finally, an SVM classification model was constructed for predicting PPIs. Experimental results exhibit that our method precedes those previously published in the literature. |
| Databáze: | OpenAIRE |
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