References
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.
If you use ASFP, please also cite:
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.
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.
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. [HTML]
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. [HTML]
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. [HTML]