Niu Huang

284 total papers · 13.7k total citations
128 papers, 5.3k citations indexed

About

Niu Huang is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Niu Huang has authored 128 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Molecular Biology, 36 papers in Computational Theory and Mathematics and 22 papers in Organic Chemistry. Recurrent topics in Niu Huang's work include Computational Drug Discovery Methods (36 papers), Protein Structure and Dynamics (24 papers) and Click Chemistry and Applications (11 papers). Niu Huang is often cited by papers focused on Computational Drug Discovery Methods (36 papers), Protein Structure and Dynamics (24 papers) and Click Chemistry and Applications (11 papers). Niu Huang collaborates with scholars based in China, United States and Singapore. Niu Huang's 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 Nilesh K. Banavali and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Niu Huang

120 papers receiving 5.2k citations

Hit Papers

Benchmarking Sets for Mol... 2006 2026 2012 2019 2006 2025 250 500 750 1000

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Niu Huang 3.3k 1.7k 793 626 397 128 5.3k
Glen E. Kellogg 2.9k 0.9× 1.2k 0.7× 914 1.2× 717 1.1× 346 0.9× 143 4.9k
Claudio N. Cavasotto 2.7k 0.8× 1.8k 1.0× 573 0.7× 427 0.7× 275 0.7× 85 4.1k
Andrew J. Doig 5.5k 1.7× 1.6k 0.9× 605 0.8× 1.1k 1.8× 466 1.2× 108 8.6k
Samuel Genheden 4.0k 1.2× 2.0k 1.1× 892 1.1× 913 1.5× 466 1.2× 70 6.1k
Carlos J. Camacho 4.9k 1.5× 1.7k 1.0× 557 0.7× 1.5k 2.4× 581 1.5× 119 6.8k
Matthew Lee 3.3k 1.0× 936 0.5× 533 0.7× 409 0.7× 487 1.2× 72 5.4k
Wolfgang Jahnke 3.7k 1.1× 974 0.6× 894 1.1× 676 1.1× 664 1.7× 113 5.7k
Herman van Vlijmen 3.1k 0.9× 1.3k 0.8× 402 0.5× 781 1.2× 254 0.6× 97 4.3k
Sheng‐You Huang 4.3k 1.3× 1.8k 1.1× 384 0.5× 843 1.3× 306 0.8× 116 5.9k
Paul S. Charifson 2.9k 0.9× 1.3k 0.8× 723 0.9× 464 0.7× 362 0.9× 55 4.0k

Countries citing papers authored by Niu Huang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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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.

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