One-Class Classifier to Predict Protein-Protein Interactions based on Hydrophobibity Properties
Protein-protein interactions are important in a wide range of biological processes. The development of drugs that target such interactions is a very active research field. Hence predicting protein-protein interactions represent an important challenge in bioinformatics research. Machine learning tech...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2006
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| Online Access: | http://eprints.utm.my/8755/ http://eprints.utm.my/8755/1/ISBME-2006.pdf |
| _version_ | 1848891759866675200 |
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| author | Alashwal, Hany Taher Ahmed Deris, Safaai Othman, Muhamad Razib Mohamad, Mohd. Saberi |
| author_facet | Alashwal, Hany Taher Ahmed Deris, Safaai Othman, Muhamad Razib Mohamad, Mohd. Saberi |
| author_sort | Alashwal, Hany Taher Ahmed |
| building | UTeM Institutional Repository |
| collection | Online Access |
| description | Protein-protein interactions are important in a wide range of biological processes. The development of drugs that target such interactions is a very active research field. Hence predicting protein-protein interactions represent an important challenge in bioinformatics research. Machine learning techniques have been applied to predict protein-protein interactions. Most of these techniques address this problem as a binary classification problem. While it is easy to get a dataset of interacting protein as positive example, there are no experimentally confirmed noninteracting proteins to be considered as a negative set. Therefore, in this paper we solve this problem as a one-class classification problem using One-Class SVM (OCSVM). The hydrophobicity properties have been used in this research as the protein sequence feature. Using only positive examples (interacting protein pairs) for training, the OCSVM achieves accuracy of 72% using RBF kernel. These results imply that protein-protein interaction can be predicted using oneclass classifier with reliable accuracy. |
| first_indexed | 2025-11-15T21:03:05Z |
| format | Conference or Workshop Item |
| id | utm-8755 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T21:03:05Z |
| publishDate | 2006 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-87552017-08-30T01:25:58Z http://eprints.utm.my/8755/ One-Class Classifier to Predict Protein-Protein Interactions based on Hydrophobibity Properties Alashwal, Hany Taher Ahmed Deris, Safaai Othman, Muhamad Razib Mohamad, Mohd. Saberi Protein-protein interactions are important in a wide range of biological processes. The development of drugs that target such interactions is a very active research field. Hence predicting protein-protein interactions represent an important challenge in bioinformatics research. Machine learning techniques have been applied to predict protein-protein interactions. Most of these techniques address this problem as a binary classification problem. While it is easy to get a dataset of interacting protein as positive example, there are no experimentally confirmed noninteracting proteins to be considered as a negative set. Therefore, in this paper we solve this problem as a one-class classification problem using One-Class SVM (OCSVM). The hydrophobicity properties have been used in this research as the protein sequence feature. Using only positive examples (interacting protein pairs) for training, the OCSVM achieves accuracy of 72% using RBF kernel. These results imply that protein-protein interaction can be predicted using oneclass classifier with reliable accuracy. 2006 Conference or Workshop Item PeerReviewed application/pdf en http://eprints.utm.my/8755/1/ISBME-2006.pdf Alashwal, Hany Taher Ahmed and Deris, Safaai and Othman, Muhamad Razib and Mohamad, Mohd. Saberi (2006) One-Class Classifier to Predict Protein-Protein Interactions based on Hydrophobibity Properties. In: In Proc 2nd Int'l Symp. Biomedical Engineering (ISBME'06), Bangkok, Thailand.. |
| spellingShingle | Alashwal, Hany Taher Ahmed Deris, Safaai Othman, Muhamad Razib Mohamad, Mohd. Saberi One-Class Classifier to Predict Protein-Protein Interactions based on Hydrophobibity Properties |
| title | One-Class Classifier to Predict Protein-Protein
Interactions based on Hydrophobibity Properties |
| title_full | One-Class Classifier to Predict Protein-Protein
Interactions based on Hydrophobibity Properties |
| title_fullStr | One-Class Classifier to Predict Protein-Protein
Interactions based on Hydrophobibity Properties |
| title_full_unstemmed | One-Class Classifier to Predict Protein-Protein
Interactions based on Hydrophobibity Properties |
| title_short | One-Class Classifier to Predict Protein-Protein
Interactions based on Hydrophobibity Properties |
| title_sort | one-class classifier to predict protein-protein
interactions based on hydrophobibity properties |
| url | http://eprints.utm.my/8755/ http://eprints.utm.my/8755/1/ISBME-2006.pdf |