ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots
- DOI
- 10.1021/acs.jcim.3c02011
- Published
- 2024-04-08
- Container
- Journal of Chemical Information and Modeling
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acs.jcim.3c02011,
title = {ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots},
author = {Lianci Tao and Tong Zhou and Zhixiang Wu and Fangrui Hu and Shuang Yang and Xiaotian Kong and Chunhua Li},
year = {2024},
journal = {Journal of Chemical Information and Modeling},
doi = {10.1021/acs.jcim.3c02011},
url = {https://doi.org/10.1021/acs.jcim.3c02011}
}RIS
TY - JOUR TI - ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots AU - Lianci Tao AU - Tong Zhou AU - Zhixiang Wu AU - Fangrui Hu AU - Shuang Yang AU - Xiaotian Kong AU - Chunhua Li PY - 2024 JO - Journal of Chemical Information and Modeling DO - 10.1021/acs.jcim.3c02011 UR - https://doi.org/10.1021/acs.jcim.3c02011 ER -
APA
Tao, L., Zhou, T., Wu, Z., Hu, F., Yang, S., Kong, X., & Li, C. (2024). ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots. Journal of Chemical Information and Modeling. https://doi.org/10.1021/acs.jcim.3c02011
Source records
- crossref · retrieved 2026-11-06T18:23:33.337Z