SGPPI: structure-aware prediction of protein-protein interactions in rigorous conditions with graph convolutional network.

Huang, Yan; Wuchty, Stefan; Zhou, Yuan; Zhang, Ziding

Huang, Yan; Wuchty, Stefan; Zhou, Yuan; Zhang, Ziding.

Affiliation

Huang Y; State Key Laboratory of Livestock and Poultry Biotechnology Breeding, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
Wuchty S; Department of Biomedical Informatics, Ministry of Education Key Laboratory of Molecular Cardiovascular Sciences, Center for Non-Coding RNA Medicine, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
Zhou Y; Department of Computer Science, University of Miami, Coral Gables, FL 33146, USA.
Zhang Z; Department of Biology, University of Miami, Coral Gables, FL 33146, USA.

Brief Bioinform ; 24(2)2023 03 19.

Article in En | MEDLINE | ID: mdl-36682013

Subject(s)

Machine Learning; Proteins; Humans; Proteins/chemistry; Protein Binding; Amino Acid Sequence; Saccharomyces cerevisiae/metabolism

Key words

deep learning; graph convolutional neural network; prediction; proteinprotein interaction; structure

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Proteins / Machine Learning Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Brief Bioinform Journal subject: BIOLOGIA / INFORMATICA MEDICA Year: 2023 Type: Article Affiliation country: China

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