Danishuddin; Kumar, V.; Parate, S.; Bahuguna, A.; Lee, G.; Kim, M.O.; Lee, K.W.
Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer. Pharmaceuticals 2021, 14, 699.
https://doi.org/10.3390/ph14070699
AMA Style
Danishuddin, Kumar V, Parate S, Bahuguna A, Lee G, Kim MO, Lee KW.
Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer. Pharmaceuticals. 2021; 14(7):699.
https://doi.org/10.3390/ph14070699
Chicago/Turabian Style
Danishuddin, Vikas Kumar, Shraddha Parate, Ashutosh Bahuguna, Gihwan Lee, Myeong Ok Kim, and Keun Woo Lee.
2021. "Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer" Pharmaceuticals 14, no. 7: 699.
https://doi.org/10.3390/ph14070699
APA Style
Danishuddin, Kumar, V., Parate, S., Bahuguna, A., Lee, G., Kim, M. O., & Lee, K. W.
(2021). Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer. Pharmaceuticals, 14(7), 699.
https://doi.org/10.3390/ph14070699
