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Prediction of Protein-Protein Interactions Based on Domain

Protein-protein interactions (PPIs) play a crucial role in various biological processes. To better comprehend the pathogenesis and treatments of various diseases, it is necessary to learn the detail of these interactions. However, the current experimental method still has many false-positive and fal...

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Detalles Bibliográficos
Autores principales: Li, Xue, Yang, Lifeng, Zhang, Xiaopan, Jiao, Xiong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720845/
https://www.ncbi.nlm.nih.gov/pubmed/31531123
http://dx.doi.org/10.1155/2019/5238406
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author Li, Xue
Yang, Lifeng
Zhang, Xiaopan
Jiao, Xiong
author_facet Li, Xue
Yang, Lifeng
Zhang, Xiaopan
Jiao, Xiong
author_sort Li, Xue
collection PubMed
description Protein-protein interactions (PPIs) play a crucial role in various biological processes. To better comprehend the pathogenesis and treatments of various diseases, it is necessary to learn the detail of these interactions. However, the current experimental method still has many false-positive and false-negative problems. Computational prediction of protein-protein interaction has become a more important prediction method which can overcome the obstacles of the experimental method. In this work, we proposed a novel computational domain-based method for PPI prediction, and an SVM model for the prediction was built based on the physicochemical property of the domain. The outcomes of SVM and the domain-domain score were used to construct the prediction model for protein-protein interaction. The predicted results demonstrated the domain-based research can enhance the ability to predict protein interactions.
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spelling pubmed-67208452019-09-17 Prediction of Protein-Protein Interactions Based on Domain Li, Xue Yang, Lifeng Zhang, Xiaopan Jiao, Xiong Comput Math Methods Med Research Article Protein-protein interactions (PPIs) play a crucial role in various biological processes. To better comprehend the pathogenesis and treatments of various diseases, it is necessary to learn the detail of these interactions. However, the current experimental method still has many false-positive and false-negative problems. Computational prediction of protein-protein interaction has become a more important prediction method which can overcome the obstacles of the experimental method. In this work, we proposed a novel computational domain-based method for PPI prediction, and an SVM model for the prediction was built based on the physicochemical property of the domain. The outcomes of SVM and the domain-domain score were used to construct the prediction model for protein-protein interaction. The predicted results demonstrated the domain-based research can enhance the ability to predict protein interactions. Hindawi 2019-08-21 /pmc/articles/PMC6720845/ /pubmed/31531123 http://dx.doi.org/10.1155/2019/5238406 Text en Copyright © 2019 Xue Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Xue
Yang, Lifeng
Zhang, Xiaopan
Jiao, Xiong
Prediction of Protein-Protein Interactions Based on Domain
title Prediction of Protein-Protein Interactions Based on Domain
title_full Prediction of Protein-Protein Interactions Based on Domain
title_fullStr Prediction of Protein-Protein Interactions Based on Domain
title_full_unstemmed Prediction of Protein-Protein Interactions Based on Domain
title_short Prediction of Protein-Protein Interactions Based on Domain
title_sort prediction of protein-protein interactions based on domain
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6720845/
https://www.ncbi.nlm.nih.gov/pubmed/31531123
http://dx.doi.org/10.1155/2019/5238406
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AT yanglifeng predictionofproteinproteininteractionsbasedondomain
AT zhangxiaopan predictionofproteinproteininteractionsbasedondomain
AT jiaoxiong predictionofproteinproteininteractionsbasedondomain