{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T01:02:31Z","timestamp":1775437351987,"version":"3.50.1"},"reference-count":54,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:00:00Z","timestamp":1705536000000},"content-version":"vor","delay-in-days":57,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100006407","name":"Natural Science Foundation of Henan Province","doi-asserted-by":"publisher","award":["212300410367"],"award-info":[{"award-number":["212300410367"]}],"id":[{"id":"10.13039\/501100006407","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006407","name":"Natural Science Foundation of Henan Province","doi-asserted-by":"publisher","award":["202300410102"],"award-info":[{"award-number":["202300410102"]}],"id":[{"id":"10.13039\/501100006407","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Research Key Project of Educational Department of Henan Province","award":["21A520023"],"award-info":[{"award-number":["21A520023"]}]},{"name":"Science and Technology Research Key Project of Educational Department of Henan Province","award":["22A520030"],"award-info":[{"award-number":["22A520030"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072160"],"award-info":[{"award-number":["62072160"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072157"],"award-info":[{"award-number":["62072157"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011447","name":"Science and Technology Department of Henan Province","doi-asserted-by":"publisher","award":["212102310381"],"award-info":[{"award-number":["212102310381"]}],"id":[{"id":"10.13039\/501100011447","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Educational Science Research Foundation of Henan Normal University","award":["2018JK19"],"award-info":[{"award-number":["2018JK19"]}]},{"name":"Production and Learning Cooperation and Cooperative Education Project of Ministry of Education of China","award":["202102633006"],"award-info":[{"award-number":["202102633006"]}]},{"name":"Science and Technology Department of Xinxiang City","award":["GG2021004"],"award-info":[{"award-number":["GG2021004"]}]},{"name":"State Foundation for Studying Abroad of China","award":["202008410042"],"award-info":[{"award-number":["202008410042"]}]},{"name":"High Performance Computing Center of Henan Normal University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Combination therapy has exhibited substantial potential compared to monotherapy. However, due to the explosive growth in the number of cancer drugs, the screening of synergistic drug combinations has become both expensive and time-consuming. Synergistic drug combinations refer to the concurrent use of two or more drugs to enhance treatment efficacy. Currently, numerous computational methods have been developed to predict the synergistic effects of anticancer drugs. However, there has been insufficient exploration of how to mine drug and cell line data at different granularity levels for predicting synergistic anticancer drug combinations. Therefore, this study proposes a granularity-level information fusion strategy based on the hypergraph transformer, named HypertranSynergy, to predict synergistic effects of anticancer drugs. HypertranSynergy introduces synergistic connections between cancer cell lines and drug combinations using hypergraph. Then, the Coarse-grained Information Extraction (CIE) module merges the hypergraph with a transformer for node embeddings. In the CIE module, Contranorm is a normalization layer that mitigates over-smoothing, while Gaussian noise addresses local information gaps. Additionally, the Fine-grained Information Extraction (FIE) module assesses fine-grained information\u2019s impact on predictions by employing similarity-aware matrices from drug\/cell line features. Both CIE and FIE modules are integrated into HypertranSynergy. In addition, HypertranSynergy achieved the AUC of 0.93${\\pm }$0.01 and the AUPR of 0.69${\\pm }$0.02 in 5-fold cross-validation of classification task, and the RMSE of 13.77${\\pm }$0.07 and the PCC of 0.81${\\pm }$0.02 in 5-fold cross-validation of regression task. These results are better than most of the state-of-the-art models.<\/jats:p>","DOI":"10.1093\/bib\/bbad522","type":"journal-article","created":{"date-parts":[[2024,1,19]],"date-time":"2024-01-19T02:07:17Z","timestamp":1705630037000},"source":"Crossref","is-referenced-by-count":14,"title":["A granularity-level information fusion strategy on hypergraph transformer for predicting synergistic effects of anticancer drugs"],"prefix":"10.1093","volume":"25","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"},{"name":"Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province \u00a0 453007 , China"}]},{"given":"Gaolin","family":"Yuan","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"}]},{"given":"Shitong","family":"Wan","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"}]},{"given":"Ziwei","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"}]},{"given":"Dong","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"},{"name":"Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province \u00a0 453007 , China"}]},{"given":"Hongjun","family":"Zhang","sequence":"additional","affiliation":[{"name":"Hebi Instiute of Engineering and Technology, Henan Polytechnic University , 458030 , China"}]},{"given":"Juntao","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematics and Information Science, Henan Normal University , 453007 Xinxiang , China"}]},{"given":"Yun","family":"Zhou","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Henan Normal University , 453007 Xinxiang , China"},{"name":"Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province \u00a0 453007 , China"}]},{"given":"Xianfang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Technology Engineering, Henan Institute of Technology , 453000 , China"}]}],"member":"286","published-online":{"date-parts":[[2024,1,17]]},"reference":[{"issue":"7","key":"2024011902061303900_ref1","doi-asserted-by":"crossref","first-page":"1678","DOI":"10.1016\/j.cell.2017.11.009","article-title":"Combination cancer therapy can confer benefit via patient-to-patient variability without drug additivity or 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