References
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Xujun Zhang, Chao Shen, Xueying Guo, Zhe Wang, Gaoqi Weng, Qing Ye, Gaoang Wang, Qiaojun He, Bo Yang*, Dongsheng Cao* &
Tingjun Hou*, ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions, Journal of Cheminformatics, 2021, Published.
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If you use ASFP, please also cite:
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Chao Shen, Junjie Ding, Zhe Wang, Dongsheng Cao, Xiaoqin Ding, Tingjun Hou*, From
machine learning to deep learning: advances in scoring functions for computational
docking, WIRES Computational Molecular Science,
2020, 10, e1429.
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Chao Shen, Ye Hu, Zhe Wang, Xujun Zhang, Haiyang Zhong, Gaoang Wang, Xiaojun Yao,
Lei Xu, Dongsheng Cao*, Tingjun Hou*, Can machine learning consistently improve the
scoring power of classical scoring functions? insights into the role of machine
learning in scoring functions, Briefings in Bioinformatics,
accepted.
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Zhe Wang, Huiyong Sun, Xiaojun Yao, Dan Li, Lei Xu, Youyong Li, Sheng Tian, Tingjun
Hou*, Comprehensive evaluation of ten docking programs on a diverse set of
protein-ligand complexes: prediction accuracy of sampling power and scoring
power, Physical Chemistry Chemical Physics, 2016,
18, 12964-12975.
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Huiyong Sun, Peichen Pan, Sheng Tian, Lei Xu, Xiaotian Kong, Youyong Li, Dan Li,
Tingjun Hou*, Constructing and Validating High-Performance MIEC-SVM Models in
Virtual Screening for Kinases: A Better Way for Actives Discovery, Scientific Reports, 2016, 6, 24817.
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Tingjun Hou*, Nan Li, Youyong Li, Wei Wang*, Characterization of domain-peptide
interaction interface: prediction of SH3 domain-mediated protein-protein interaction
network in yeast by generic structure-based models, Journal of Proteome Research,
2012, 11, 2982-2995.
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