{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Li Y"],"funding":["Shanxi Province Science Foundation for Youths","Natural Science Foundation of Shanxi","Foundation for Innovative Research Groups of the National Natural Science Foundation of China","National Natural Science Foundation of China","Research Project Supported by Shanxi Scholarship Council of China","National Key Scientific and Technological Infrastructure project \"Earth System Numerical Simulation Facility\"","National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility”"],"pagination":["25054"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11499656"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["14(1)"],"pubmed_abstract":["Accurate prediction of drug-target interactions (DTIs) is crucial for advancing drug discovery and repurposing. Computational methods have significantly improved the efficiency of experimental predictions for drug-target interactions in Western medicine. However, accurately predicting the complex relationships between Chinese medicine ingredients and targets remains a formidable challenge due to the vast number and high heterogeneity of these ingredients. In this study, we introduce the CWI-DTI method, which achieves high-accuracy prediction of DTIs using a large dataset of interactive relationships of drug ingredients or candidate targets. Moreover, we present a novel dataset to evaluate the prediction accuracy of both Chinese and Western medicine. Through meticulous collection and prepro"],"journal":["Scientific reports"],"pubmed_title":["Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model."],"pmcid":["PMC11499656"],"funding_grant_id":["20210302123092","62403344","62176177","2021-039","20210302123112","2023-EL-PT-000371, 2023-EL-PT-000374"],"pubmed_authors":["Yang H","Liu Y","Li Y","Chen Z","Wang B","Zhang X","Xiang J","Yan T","Wang H"],"additional_accession":[]},"is_claimable":false,"name":"Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model.","description":"Accurate prediction of drug-target interactions (DTIs) is crucial for advancing drug discovery and repurposing. Computational methods have significantly improved the efficiency of experimental predictions for drug-target interactions in Western medicine. However, accurately predicting the complex relationships between Chinese medicine ingredients and targets remains a formidable challenge due to the vast number and high heterogeneity of these ingredients. In this study, we introduce the CWI-DTI method, which achieves high-accuracy prediction of DTIs using a large dataset of interactive relationships of drug ingredients or candidate targets. Moreover, we present a novel dataset to evaluate the prediction accuracy of both Chinese and Western medicine. Through meticulous collection and prepro","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Oct","modification":"2025-04-26T00:14:42.208Z","creation":"2025-04-06T09:39:33.379Z"},"accession":"S-EPMC11499656","cross_references":{"pubmed":["39443630"],"doi":["10.1038/s41598-024-76367-0"]}}