Unknown

Dataset Information

0

Prediction of Protein-Protein Interactions Based on Domain.


ABSTRACT: 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.

SUBMITTER: Li X 

PROVIDER: S-EPMC6720845 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

altmetric image

Publications

Prediction of Protein-Protein Interactions Based on Domain.

Li Xue X   Yang Lifeng L   Zhang Xiaopan X   Jiao Xiong X  

Computational and mathematical methods in medicine 20190821


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, w  ...[more]

Similar Datasets

| S-EPMC5335770 | biostudies-literature
| S-EPMC6423278 | biostudies-other
| S-EPMC2905371 | biostudies-literature
| S-EPMC1919395 | biostudies-literature
| S-EPMC4333188 | biostudies-literature
| S-EPMC3482288 | biostudies-literature
| S-EPMC7372763 | biostudies-literature