Advances in Computational Methods for Protein–Protein Interaction Prediction
Protein–protein interactions (PPIs) are pivotal in various physiological processes inside biological entities. Accurate identification of PPIs holds paramount significance for comprehending biological processes, deciphering disease mechanisms, and advancing medical research. Given the costly and lab...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-03-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/13/6/1059 |
| _version_ | 1797241356483035136 |
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| author | Lei Xian Yansu Wang |
| author_facet | Lei Xian Yansu Wang |
| author_sort | Lei Xian |
| collection | DOAJ |
| description | Protein–protein interactions (PPIs) are pivotal in various physiological processes inside biological entities. Accurate identification of PPIs holds paramount significance for comprehending biological processes, deciphering disease mechanisms, and advancing medical research. Given the costly and labor-intensive nature of experimental approaches, a multitude of computational methods have been devised to enable swift and large-scale PPI prediction. This review offers a thorough examination of recent strides in computational methodologies for PPI prediction, with a particular focus on the utilization of deep learning techniques within this domain. Alongside a systematic classification and discussion of relevant databases, feature extraction strategies, and prominent computational approaches, we conclude with a thorough analysis of current challenges and prospects for the future of this field. |
| first_indexed | 2024-04-24T18:22:02Z |
| format | Article |
| id | doaj.art-15454fe021d247acaf03ac3437718698 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-04-24T18:22:02Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-15454fe021d247acaf03ac34377186982024-03-27T13:34:52ZengMDPI AGElectronics2079-92922024-03-01136105910.3390/electronics13061059Advances in Computational Methods for Protein–Protein Interaction PredictionLei Xian0Yansu Wang1Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, ChinaInstitute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 611731, ChinaProtein–protein interactions (PPIs) are pivotal in various physiological processes inside biological entities. Accurate identification of PPIs holds paramount significance for comprehending biological processes, deciphering disease mechanisms, and advancing medical research. Given the costly and labor-intensive nature of experimental approaches, a multitude of computational methods have been devised to enable swift and large-scale PPI prediction. This review offers a thorough examination of recent strides in computational methodologies for PPI prediction, with a particular focus on the utilization of deep learning techniques within this domain. Alongside a systematic classification and discussion of relevant databases, feature extraction strategies, and prominent computational approaches, we conclude with a thorough analysis of current challenges and prospects for the future of this field.https://www.mdpi.com/2079-9292/13/6/1059protein–protein interactionscomputational methodsbiological informationfeature extraction |
| spellingShingle | Lei Xian Yansu Wang Advances in Computational Methods for Protein–Protein Interaction Prediction Electronics protein–protein interactions computational methods biological information feature extraction |
| title | Advances in Computational Methods for Protein–Protein Interaction Prediction |
| title_full | Advances in Computational Methods for Protein–Protein Interaction Prediction |
| title_fullStr | Advances in Computational Methods for Protein–Protein Interaction Prediction |
| title_full_unstemmed | Advances in Computational Methods for Protein–Protein Interaction Prediction |
| title_short | Advances in Computational Methods for Protein–Protein Interaction Prediction |
| title_sort | advances in computational methods for protein protein interaction prediction |
| topic | protein–protein interactions computational methods biological information feature extraction |
| url | https://www.mdpi.com/2079-9292/13/6/1059 |
| work_keys_str_mv | AT leixian advancesincomputationalmethodsforproteinproteininteractionprediction AT yansuwang advancesincomputationalmethodsforproteinproteininteractionprediction |