Thermal proteome profiling and machine learning modeling for dissecting chemical-protein interactions in environmental toxicology: A mini-review and perspectives-Reference-Cited by-同舟云学术

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Thermal proteome profiling and machine learning modeling for dissecting chemical-protein interactions in environmental toxicology: A mini-review and perspectives

Published:2024-02-26 Issue:20 Volume:54 Page:1478-1500
ISSN:1064-3389
Container-title:Critical Reviews in Environmental Science and Technology
language:en
Short-container-title:Critical Reviews in Environmental Science and Technology

Author:

Wu Zimeng¹,Fu Zhiqiang¹,Yu Xiaomei¹,Chen Jingwen¹

Affiliation:

1. Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian, China

Funder

National Natural Science Foundation of China

National Key R&D Program of China

Open Foundation of Key Laboratory of Industrial Ecology and Environmental Engineering, MOE

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/10643389.2024.2320753

Reference124 articles.

1. DeepCDA: deep cross-domain compound–protein affinity prediction through LSTM and convolutional neural networks

2. Permutation importance: a corrected feature importance measure

3. Machine learning approaches and databases for prediction of drug–target interaction: a survey paper

4. Chemoproteomic approaches to drug target identification and drug profiling

5. Revealing promiscuous drug–target interactions by chemical proteomics

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