Application of DNA-Binding Protein Prediction Based on Graph Convolutional Network and Contact Map. (17th January 2022)

• Record Type: Journal Article
• Authors: Lu, Weizhong; Zhou, Nan; Ding, Yijie; Wu, Hongjie; Zhang, Yu; Fu, Qiming; Li, Haiou
• Other Names: Thai Khac-Minh Academic Editor.
• Is Part Of: BioMed research international. Volume 2022(2022)
• Publication Date: 2022-01-17
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2022/9044793
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : DNA contains the genetic information for the synthesis of proteins and RNA, and it is an indispensable substance in living organisms. DNA-binding proteins are an enzyme, which can bind with DNA to produce complex proteins, and play an important role in the functions of a variety of biological molecules. With the continuous development of deep learning, the introduction of deep learning into DNA-binding proteins for prediction is conducive to improving the speed and accuracy of DNA-binding protein recognition. In this study, the features and structures of proteins were used to obtain their representations through graph convolutional networks. A protein prediction model based on graph convolutional network and contact map was proposed. The method had some advantages by testing various indexes of PDB14189 and PDB2272 on the benchmark dataset.