Niu Huang
- Molecular Biology top 2%
- Computational Theory and Mathematics top 0.2%
- Organic Chemistry top 2%
- Materials Chemistry top 10%
- Oncology top 10%
- Co-authors
- Brian K. ShoichetJohn J. IrwinAlexander D. MacKerellMatthew P. JacobsonChakrapani KalyanaramanYunfei DuKatarzyna BernackiJincai Yang
- Topics
- Computational Drug Discovery Methods (37 papers)Protein Structure and Dynamics (24 papers)Click Chemistry and Applications (11 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Niu Huang
121 papers receiving 5.3k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Molecular Biology 3.3k
- Computational Theory and Mathematics 1.8k
- Organic Chemistry 808
- Materials Chemistry 632
- Oncology 403
Countries citing papers authored by Niu Huang
This map shows the geographic impact of Niu Huang'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 Niu Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Niu Huang more than expected).
Fields of papers citing papers by Niu Huang
This network shows the impact of papers produced by Niu Huang. 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 Niu Huang. The network helps show where Niu Huang may publish in the future.
Co-authorship network of co-authors of Niu Huang
This figure shows the co-authorship network connecting the top 25 collaborators of Niu Huang. A scholar is included among the top collaborators of Niu Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Niu Huang. Niu Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 5 | |
| 9 | 0 | |
| 10 | 26 | |
| 11 | 31 | |
| 12 | 16 | |
| 13 | Hydrocortisone Suppresses Early Paraneoplastic Inflammation And Angiogenesis To Attenuate Early Hepatocellular Carcinoma Progression In Rats | 2 |
| 14 | Inhibition of KPNB1 Inhibits Proliferation and Promotes Apoptosis of Chronic Myeloid Leukemia Cells Through Regulation of E2F1 | 1 |
| 15 | A meta-analysis of the efficacy and safety of PD-1/PD-L1 immune checkpoint inhibitors as treatments for metastatic bladder cancer | 1 |
| 16 | Dihydrodiosgenin inhibits endothelial cell-derived factor VIII and platelet-mediated hepatocellular carcinoma metastasis | 3 |
| 17 | 54 | |
| 18 | 18 | |
| 19 | 8 | |
| 20 | 24 |
About Niu Huang
Niu Huang is a scholar working on Computational Theory and Mathematics, Molecular Biology and Organic Chemistry, having authored 130 papers that have together received 5.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (37 papers), Protein Structure and Dynamics (24 papers) and Click Chemistry and Applications (11 papers). The work is most often cited by research in Computational Theory and Mathematics (1.8k citations), Molecular Biology (3.3k citations) and Organic Chemistry (808 citations). Niu Huang has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Brian K. Shoichet, John J. Irwin, Alexander D. MacKerell, Matthew P. Jacobson, Chakrapani Kalyanaraman, Yunfei Du, Katarzyna Bernacki, Jincai Yang, L. A. Heppel and Yuanxun Wang. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.