Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Hyun-Kil Shin"'
Autor:
Hyun Kil Shin
Publikováno v:
ACS Omega, Vol 6, Iss 51, Pp 35757-35768 (2021)
Externí odkaz:
https://doaj.org/article/7e95c8043d25437f8faad1ff7f21accd
Publikováno v:
ACS Omega, Vol 6, Iss 23, Pp 15361-15373 (2021)
Externí odkaz:
https://doaj.org/article/32b8d6968ac54907b533b4def88b088b
Publikováno v:
Journal of Cheminformatics, Vol 12, Iss 1, Pp 1-17 (2020)
Abstract Computer-aided research on the relationship between molecular structures of natural compounds (NC) and their biological activities have been carried out extensively because the molecular structures of new drug candidates are usually analogou
Externí odkaz:
https://doaj.org/article/e84d7d95739b437ba38ea19d73cae166
Publikováno v:
Frontiers in Pharmacology, Vol 11 (2020)
Drug-induced liver injury (DILI) is one of the major reasons for termination of drug development. Due to the importance of predicting DILI in early phases of drug development, diverse in silico models have been developed to filter out DILI-causing ca
Externí odkaz:
https://doaj.org/article/99e6c26044fe4c3b9375b10149e825df
Publikováno v:
Molecular & Cellular Toxicology. 18:299-309
Background Dog-associated infections are related to more than 70 human diseases. Given that the health diagnosis of a dog requires expertise of the veterinarian, an artificial intelligence model for detecting dog diseases could significantly reduce t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4833565234e4b56e1b63b9c151e9d984
https://doi.org/10.1007/s13273-022-00249-7
https://doi.org/10.1007/s13273-022-00249-7
Publikováno v:
Toxicological Research. 38:393-407
Drug-induced liver injury (DILI) is one of the leading reasons for discontinuation of a new drug development project. Diverse machine learning or deep learning models have been developed to predict DILI. However, these models have not provided an ade
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b9f4aa1db5b52c41376d71d717a13fd
https://doi.org/10.1007/s43188-022-00124-6
https://doi.org/10.1007/s43188-022-00124-6
Publikováno v:
ACS Omega
ACS Omega, Vol 6, Iss 23, Pp 15361-15373 (2021)
ACS Omega, Vol 6, Iss 23, Pp 15361-15373 (2021)
The objective of this study was to develop a robust prediction model for the infinite dilution activity coefficients (γ∞) of organic molecules in diverse ionic liquid (IL) solvents. Electrostatic, hydrogen bond, polarizability, molecular structure
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1a69890fadf347a0aa3eee1ce49780f
http://europepmc.org/articles/PMC8210453
http://europepmc.org/articles/PMC8210453
Autor:
Hyun Kil Shin
Publikováno v:
RSC Advances. 10:33268-33278
Registration, evaluation, and authorization of chemicals (REACH), the regulation of chemicals in use, imposes the characterization and report of the physicochemical properties of compounds. To cope with the financial burden of the experiments, the us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6702915a2fe35d5dc1a897758bef7ffd
https://doi.org/10.1039/d0ra05873d
https://doi.org/10.1039/d0ra05873d
Autor:
Hyun Kil Shin, Hang-Suk Chun, Sangwoo Lee, Se-Myo Park, Daeui Park, Myung-Gyun Kang, Sungbo Hwang, Jung-Hwa Oh, Hyoung-Yun Han, Woo-Keun Kim, Seokjoo Yoon
Publikováno v:
Bioinformatics (Oxford, England). 38(18)
Summary Drug-induced liver injury (DILI) is a challenging endpoint in predictive toxicology because of the complex reactive metabolites that cause liver damage and the wide range of mechanisms involved in the development of the disease. ToxSTAR provi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::18f02001f45ed4845fc117aacdf26aa2
https://pubmed.ncbi.nlm.nih.gov/35900148
https://pubmed.ncbi.nlm.nih.gov/35900148
Autor:
Hyun Kil Shin
Owing to the success achieved by deep learning, researchers are exploringthe application of deep learning in drug discovery to improve the accuracy of prediction models. Significant performance improvement has been achieved by diverse convolutional n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de8c476960d6f65fa2afa1a6ed889aee
https://doi.org/10.21203/rs.3.rs-709747/v1
https://doi.org/10.21203/rs.3.rs-709747/v1
