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Experimental validation of drug responses predicted by deep learning-based bioactivity models in hepatocellular carcinoma cell lines
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HIBIT22_paper_33.pdf
Date
2022-10
Author
Akar, Etkin
Ozcan, Umut Onur
Mohammadvand, Navid
Doğan, Tunca
Kahraman, Deniz Cansen
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Hepatocellular carcinoma (HCC) is one of the deadliest cancers worldwide. Although it has high mortality rate, there are currently few drugs available as treatment options. Therefore, there is an urgent need for intensive basic research and clinical trials in HCC. With the utilization of computational predictive approaches, effective treatment strategies, which leverage target-based drug response predictions, can be developed. This study aims to validate the results of deep learning-based prediction method, DeepResponse, developed by “Biological Data Science Lab” at Hacettepe University, and propose small molecule inhibitors that are active against HCC cell lines.
URI
https://hibit2022.ims.metu.edu.tr
https://hdl.handle.net/11511/101993
Conference Name
The International Symposium on Health Informatics and Bioinformatics
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Graduate School of Informatics, Conference / Seminar
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E. Akar, U. O. Ozcan, N. Mohammadvand, T. Doğan, and D. C. Kahraman, “Experimental validation of drug responses predicted by deep learning-based bioactivity models in hepatocellular carcinoma cell lines,” Erdemli, Mersin, TÜRKİYE, 2022, p. 3033, Accessed: 00, 2023. [Online]. Available: https://hibit2022.ims.metu.edu.tr.