Target identification among known drugs by deep learning from heterogeneous networks is a research paper published in Chemical Science (2020). On theSindex it has a DataRank of 0. It has been cited 354 times.
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Foundation for the National Institutes of Health
Grant: HHSN261200800001E
National Institute of Neurological Disorders and Stroke
Grant: R3509730
National Heart, Lung, and Blood Institute
Grant: HG007690
National Heart, Lung, and Blood Institute
Grant: HL119145
National Heart, Lung, and Blood Institute
Grant: HL61795
National Heart, Lung, and Blood Institute
Grant: K99HL138272
National Heart, Lung, and Blood Institute
Grant: R00HL138272
American Heart Association
Grant: 2017D007382
NHLBI NIH HHS
Grant: R37 HL061795
NHLBI NIH HHS
Grant: U54 HL119145
NHLBI NIH HHS
Grant: R01 HL061795
CCR NIH HHS
Grant: HHSN261200800001C
NHGRI NIH HHS
Grant: U01 HG007690
Influential Citations
16
Fields of Study
Additional file 1 of iTTCA-RF: a random forest predictor for tumor T cell antigens
Additional file 1 of iTTCA-RF: a random forest predictor for tumor T cell antigens
Additional file 1 of An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model
Additional file 1 of An end-to-end method for predicting compound-protein interactions based on simplified homogeneous graph convolutional network and pre-trained language model
Additional file 2 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation
Additional file 2 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation
Additional file 1 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation
Additional file 1 of DLDTI: a learning-based framework for drug-target interaction identification using neural networks and network representation