Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE-Reference-Cited by-同舟云学术

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Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE

Published:2023-05-01 Issue:3 Volume:20 Page:2190-2199
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Jiang Changkun¹^ORCID,Lv Weipeng¹^ORCID,Li Jianqiang¹^ORCID

Affiliation:

1. College of Computer Science and Software Engineering and the National Engineering Laboratory for Big Data System Computing Technology, Shenzhen University, Shenzhen, Guangdong Province, China

Funder

National Key R&D Program of China

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province-Outstanding Youth Program

Basic Research Project of Shenzhen Science and Technology Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/10144451/10021861.pdf?arnumber=10021861

Reference44 articles.

1. EGRET: edge aggregated graph attention networks and transfer learning improve protein–protein interaction site prediction

2. SCRIBER: accurate and partner type-specific prediction of protein-binding residues from proteins sequences

3. Protein-Protein Interaction Detection: Methods and Analysis

4. PSAIA – Protein Structure and Interaction Analyzer

5. Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein–protein interaction sites

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