H. C. Stephen Chan

2.9k citations
33 papers · 1.9k indexed · 2 hit papers · h-index 20

H. C. Stephen Chan

33 papers receiving 1.9k citations

Hit Papers

Advancing Drug Discovery via Artificial Intelligence4002017202620202023200400600

Peers

H. C. Stephen Chan
Comparison fields: 5 of 154
  • Computational Theory and Mathematics 508
  • Physical and Theoretical Chemistry 251
  • Health Informatics 34
  • Molecular Biology 983
  • Cellular and Molecular Neuroscience 173
Replace José S. Duca with:
José S. Duca United States
Ting Shi China
Káthia M. Honório Brazil
S. Barret Kalindjian United Kingdom
Shuguang Yuan China
Andrea Volkamer Germany
Trent E. Balius United States
Mahendra Awale Switzerland
Kimberley M. Zorn United States
Eugene V. Radchenko Russia
H. C. Stephen Chan relative to José S. Duca United States José S. Duca's profile →
Citations per field
00.5×3.3×
José S. Duca · 1×
Citations per year

Countries citing papers authored by H. C. Stephen Chan

Since Specialization
Citations

This map shows the geographic impact of H. C. Stephen Chan'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 H. C. Stephen Chan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites H. C. Stephen Chan more than expected).

Fields of papers citing papers by H. C. Stephen Chan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. C. Stephen Chan. 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 H. C. Stephen Chan. The network helps show where H. C. Stephen Chan may publish in the future.

Co-authorship network

The 25 scholars most cited alongside H. C. Stephen Chan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with H. C. Stephen Chan Line = papers co-authored together H. C. Stephen Chan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20231
2 20232
3 20227
4 202123
5 202027
6 201999
7
Advancing Drug Discovery via Artificial Intelligencebreakdown →
2019400
8
Using PyMOL as a platform for computational drug designbreakdown →
2017617
9 201727
10 201756
11 201713
12 201640
13 20163
14 201651
15 201438
16 201150
17 201115
18 201115
19 20119
20 196632

About H. C. Stephen Chan

H. C. Stephen Chan is a scholar working on Physical and Theoretical Chemistry, Computational Theory and Mathematics and Physiology, having authored 33 papers that have together received 1.9k indexed citations. Recurring topics across this work include Crystallography and molecular interactions (10 papers), Receptor Mechanisms and Signaling (10 papers), Computational Drug Discovery Methods (8 papers), Crystallization and Solubility Studies (7 papers), Neuropeptides and Animal Physiology (6 papers), Protein Structure and Dynamics (4 papers), X-ray Diffraction in Crystallography (4 papers) and Enzyme Structure and Function (4 papers). The work is most often cited by research in Computational Theory and Mathematics (508 citations), Physical and Theoretical Chemistry (251 citations) and Health Informatics (34 citations). H. C. Stephen Chan has collaborated with scholars based in China, United Kingdom and Switzerland. Frequent co-authors include Shuguang Yuan, Zhenquan Hu, Horst Vogel, Thamani Dahoun, Hanbin Shan, John Kendrick, Frank J. J. Leusen, Sławomir Filipek, Marcus A. Neumann and Krzysztof Palczewski. Their work appears in journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and Nature Communications.

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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