Predicting drug–protein interaction using quasi-visual question answering system

Shuangjia Zheng(Shanghai Institute of Materia Medica), Yuedong Yang(Guangzhou Experimental Station), Sheng Chen(Sun Yat-sen University), Jun Xu(Sun Yat-sen University), Yongjian Li(Sun Yat-sen University)
Nature Machine Intelligence
February 14, 2020
10.1038/s42256-020-0152-y
Cited by 303

Related Papers

Deep Learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) With CT Images
|IEEE/ACM Transactions on Computational Biology and Bioinformatics|2021|836
Capturing non-local interactions by long short-term memory bidirectional recurrent neural networks for improving prediction of protein secondary structure, backbone angles, contact numbers and solvent accessibility
|Bioinformatics|2017|389
Improving prediction of secondary structure, local backbone angles and solvent accessible surface area of proteins by iterative deep learning
|Scientific Reports|2015|365
Improving protein fold recognition and template-based modeling by employing probabilistic-based matching between predicted one-dimensional structural properties of query and corresponding native properties of templates
|Bioinformatics|2011|334
Deep learning Enables Accurate Diagnosis of Novel Coronavirus (COVID-19) with CT images
|medRxiv|2020|334