Tingjun Hou
Impact in
- Computational Theory and Mathematics top 0.01%
- Computational Drug Discovery Methods
- Molecular Biology top 0.1%
- Protein Structure and Dynamics
- Receptor Mechanisms and Signaling
- RNA and protein synthesis mechanisms
- Protein Degradation and Inhibitors
Papers in
-
- Protein Structure and Dynamics 121
- Receptor Mechanisms and Signaling 33
- Chemical Synthesis and Analysis 33
- RNA and protein synthesis mechanisms 25
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- Computational Drug Discovery Methods 259
- Co-authors
- Youyong Li (149 shared papers)Junmei Wang (52 shared papers)Huiyong Sun (87 shared papers)Zhe Wang (60 shared papers)Dongsheng Cao (80 shared papers)Lei Xu (68 shared papers)Wei Wang (4 shared papers)Sheng Tian (31 shared papers)
- Journals
- Journal of Chemical Information and Modeling (70 papers)Briefings in Bioinformatics (33 papers)Journal of Medicinal Chemistry (31 papers)Physical Chemistry Chemical Physics (22 papers)Journal of Cheminformatics (22 papers)
- Partner nations
- ChinaUnited StatesMacao
In The Last Decade
Tingjun Hou
541 papers receiving 30.3k citations
Tingjun Hou's Hit Papers
Peers
Comparison fields: 5 of 204
- Computational Theory and Mathematics 10.5k
- Molecular Biology 15.7k
- Pharmacology 1.4k
- Toxicology 429
- Organic Chemistry 3.8k
Countries citing papers authored by Tingjun Hou
This map shows the geographic impact of Tingjun Hou's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tingjun Hou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tingjun Hou more than expected).
Fields of papers citing papers by Tingjun Hou
This network shows the impact of papers produced by Tingjun Hou. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tingjun Hou. The network helps show where Tingjun Hou may publish in the future.
Co-authors
The 25 scholars most cited alongside Tingjun Hou, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 559 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Assessing the Performance of the MM/PBSA and MM/GBSA Methods. 1. The Accuracy of Binding Free Energy Calculations Based on Molecular Dynamics Simulations Hit paper breakdown → | 2010 | 2164 |
| 2 | ADMETlab 2.0: an integrated online platform for accurate and comprehensive predictions of ADMET properties Hit paper breakdown → | 2021 | 1858 |
| 3 | End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design Hit paper breakdown → | 2019 | 1550 |
| 4 | Comprehensive evaluation of ten docking programs on a diverse set of protein–ligand complexes: the prediction accuracy of sampling power and scoring power Hit paper breakdown → | 2016 | 720 |
| 5 | Assessing the performance of the molecular mechanics/Poisson Boltzmann surface area and molecular mechanics/generalized Born surface area methods. II. The accuracy of ranking poses generated from docking Hit paper breakdown → | 2010 | 643 |
| 6 | Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set Hit paper breakdown → | 2014 | 626 |
| 7 | ADMETlab 3.0: an updated comprehensive online ADMET prediction platform enhanced with broader coverage, improved performance, API functionality and decision support Hit paper breakdown → | 2024 | 483 |
| 8 | Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring Hit paper breakdown → | 2014 | 463 |
| 9 | HawkDock: a web server to predict and analyze the protein–protein complex based on computational docking and MM/GBSA Hit paper breakdown → | 2019 | 443 |
| 10 | Assessing the Performance of MM/PBSA and MM/GBSA Methods. 3. The Impact of Force Fields and Ligand Charge Models Hit paper breakdown → | 2013 | 421 |
| 11 | Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models Hit paper breakdown → | 2021 | 412 |
| 12 | Assessing the performance of the MM/PBSA and MM/GBSA methods. 6. Capability to predict protein–protein binding free energies and re-rank binding poses generated by protein–protein docking Hit paper breakdown → | 2016 | 380 |
| 13 | The application of in silico drug-likeness predictions in pharmaceutical research Hit paper breakdown → | 2015 | 376 |
| 14 | 2006 | 313 | |
| 15 | 2018 | 306 | |
| 16 | 2018 | 276 | |
| 17 | 2007 | 241 | |
| 18 | 2002 | 222 | |
| 19 | 2012 | 192 | |
| 20 | 2003 | 186 |
About Tingjun Hou
Tingjun Hou is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry and Oncology, having authored 559 papers that have together received 30.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (259 papers), Protein Structure and Dynamics (121 papers), Machine Learning in Materials Science (79 papers), Receptor Mechanisms and Signaling (33 papers), Chemical Synthesis and Analysis (33 papers), Analytical Chemistry and Chromatography (26 papers), RNA and protein synthesis mechanisms (25 papers) and Estrogen and related hormone effects (24 papers). The work is most often cited by research in Computational Theory and Mathematics (10.5k citations), Molecular Biology (15.7k citations), Pharmacology (1.4k citations), Toxicology (429 citations) and Organic Chemistry (3.8k citations). Tingjun Hou has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Youyong Li, Junmei Wang, Huiyong Sun, Zhe Wang, Dongsheng Cao, Lei Xu, Wei Wang, Sheng Tian, Dan Li and Ercheng Wang. Their work appears in journals such as Journal of Chemical Information and Modeling, Briefings in Bioinformatics, Journal of Medicinal Chemistry, Physical Chemistry Chemical Physics and Journal of Cheminformatics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.