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QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.

L. Fu, Z. Yang, Z. Yang, M. Yin, A. Lu, X. Chen, S. Liu, T. Hou, and D. Cao. Briefings Bioinform., (2021)

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Changbao Hou

Bo Hou

Lei Hou

Lijian Hou

Dongchao Hou

Other publications of authors with the same name

Molecular docking studies of a group of hydroxamate inhibitors with gelatinase-A by molecular dynamics.T. Hou, W. Zhang, and X. Xu. J. Comput. Aided Mol. Des., 16 (1): 27-41 (2002)Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n-octanol-water partition coefficient (logP) for druglike molecules using MM-PBSA method.Y. Sun, T. Hou, X. He, V. Man, and J. Wang. J. Comput. Chem., 44 (13): 1300-1311 (2023)Development and test of highly accurate endpoint free energy methods. 1: Evaluation of ABCG2 charge model on solvation free energy prediction and optimization of atom radii suitable for more accurate solvation free energy prediction by the PBSA method.Y. Sun, X. He, T. Hou, L. Cai, V. Man, and J. Wang. J. Comput. Chem., 44 (14): 1334-1346 (2023)On the Dynamic Mechanism of Long-Flexible Fatty Acid Binding to Fatty Acid Binding Protein: Resolving the Long-Standing Debate.H. Chen, Y. Guo, S. Ye, J. Zhang, H. Zhang, N. Liu, R. Zhou, T. Hou, H. Xia, Y. Kang and 1 other author(s). J. Chem. Inf. Model., 63 (16): 5232-5243 (August 2023)Improving Docking-Based Virtual Screening Ability by Integrating Multiple Energy Auxiliary Terms from Molecular Docking Scoring.W. Ye, C. Shen, G. Xiong, J. Ding, A. Lu, T. Hou, and D. Cao. J. Chem. Inf. Model., 60 (9): 4216-4230 (2020)ALipSol: An Attention-Driven Mixture-of-Experts Model for Lipophilicity and Solubility Prediction.J. Wu, J. Wang, Z. Wu, S. Zhang, Y. Deng, Y. Kang, D. Cao, C. Hsieh, and T. Hou. J. Chem. Inf. Model., 62 (23): 5975-5987 (2022)Systematic Modeling of log D7.4 Based on Ensemble Machine Learning, Group Contribution, and Matched Molecular Pair Analysis.L. Fu, L. Liu, Z. Yang, P. Li, J. Ding, Y. Yun, A. Lu, T. Hou, and D. Cao. J. Chem. Inf. Model., 60 (1): 63-76 (2020)From Black Boxes to Actionable Insights: A Perspective on Explainable Artificial Intelligence for Scientific Discovery.Z. Wu, J. Chen, Y. Li, Y. Deng, H. Zhao, C. Hsieh, and T. Hou. J. Chem. Inf. Model., 63 (24): 7617-7627 (December 2023)Out-of-the-box deep learning prediction of quantum-mechanical partial charges by graph representation and transfer learning.D. Jiang, H. Sun, J. Wang, C. Hsieh, Y. Li, Z. Wu, D. Cao, J. Wu, and T. Hou. Briefings Bioinform., (2022)Can machine learning consistently improve the scoring power of classical scoring functions? Insights into the role of machine learning in scoring functions.C. Shen, Y. Hu, Z. Wang, X. Zhang, H. Zhong, G. Wang, X. Yao, L. Xu, D. Cao, and T. Hou. Briefings Bioinform., 22 (1): 497-514 (2021)

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Disambiguation of "Hou, Tingjun"

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QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.

Please choose a person to relate this publication to

Changbao Hou

Bo Hou

Lei Hou

Lijian Hou

Dongchao Hou

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Hou, Tingjun"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.

Please choose a person to relate this publication to

Changbao Hou

Bo Hou

Lei Hou

Lijian Hou

Dongchao Hou

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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QSAR-assisted-MMPA to expand chemical transformation space for lead optimization.