Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer

Development of Machine Learning Models for Accurately Predicting and Ranking the Activity of Lead Molecules to Inhibit PRC2 Dependent Cancer

Disruption of epigenetic processes to eradicate tumor cells is among the most promising interventions for cancer control. EZH2 (Enhancer of zeste homolog 2), a catalytic component of polycomb repressive complex 2 (PRC2), methylates lysine 27 of histone H3 to promote transcriptional silencing and is...

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Những tác giả chính: Danishuddin, Vikas Kumar, Shraddha Parate, Ashutosh Bahuguna, Gihwan Lee, Myeong Ok Kim, Keun Woo Lee
Định dạng: Bài viết
Ngôn ngữ:English
Được phát hành: MDPI AG 2021-07-01
Loạt:Pharmaceuticals
Những chủ đề:
cancer
epigenetic
PRC2
machine learning
multi-class models
Truy cập trực tuyến:https://www.mdpi.com/1424-8247/14/7/699

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https://www.mdpi.com/1424-8247/14/7/699

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