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Title |
Prediction of Protein-Protein Interactions from Sequences using a Correlation Matrix of the Physicochemical Properties of Amino Acids |
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Author |
Charlemagne N’Diffon Kopoin, Armand Kodjo Atiampo, Behou Gerard N’Guessan, and Michel Babri |
| Citation |
Vol. 21 No. 3 pp. 41-47 |
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Abstract |
Detection of protein-protein interactions (PPIs) remains essential for the development of therapies against diseases. Experimental studies to detect PPI are longer and more expensive. Today, with the availability of PPI data, several computer models for predicting PPIs have been proposed. One of the big challenges in this task is feature extraction. The relevance of the information extracted by some extraction techniques remains limited. In this work, we first propose an extraction method based on correlation relationships between the physicochemical properties of amino acids. The proposed method uses a correlation matrix obtained from the hydrophobicity and hydrophilicity properties that it then integrates in the calculation of the bigram. Then, we use the SVM algorithm to detect the presence of an interaction between 2 given proteins. Experimental results show that the proposed method obtains better performances compared to the approaches in the literature. It obtains performances of 94.75% in accuracy, 95.12% in precision and 96% in sensitivity on human HPRD protein data. |
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Keywords |
Feature extraction, bigram, NLP, protein-protein interaction |
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