Cunliang Geng

1.4k citations
19 papers · 800 indexed · h-index 13

Cunliang Geng

19 papers receiving 790 citations

Peers

Cunliang Geng
Comparison fields: 5 of 104
  • Computational Theory and Mathematics 217
  • Molecular Biology 588
  • Biotechnology 64
  • Infectious Diseases 74
  • Aquatic Science 25
Replace Charles David with:
Charles David New Zealand
Ramachandran Vijayan India
Lyra Chang United States
Kuo‐Chen Chou United States
Chia-Cheng Chou Taiwan
Edwin H. Rydberg Canada
Tyler W. H. Backman United States
Nicola Bordin United Kingdom
Guy Nimrod Israel
Lucas A. Defelipe Argentina
Cunliang Geng relative to Charles David New Zealand Charles David's profile →
Citations per field
00.5×4.2×
Charles David · 1×
Citations per year

Countries citing papers authored by Cunliang Geng

Since Specialization
Citations

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

Fields of papers citing papers by Cunliang Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cunliang Geng. 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 Cunliang Geng. The network helps show where Cunliang Geng may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Cunliang Geng, 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 Cunliang Geng Line = papers co-authored together Cunliang Geng links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 20241
2 20238
3 20222
4 202176
5 202065
6 20204
7 20201
8 20204
9 201954
10 201971
11 201913
12 201856
13 2018172
14 2017100
15 201734
16 201622
17 201642
18 201327
19 201248

About Cunliang Geng

Cunliang Geng is a scholar working on Computational Theory and Mathematics, Biotechnology, Molecular Biology, Applied Psychology and Biophysics, having authored 19 papers that have together received 800 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (12 papers), Computational Drug Discovery Methods (6 papers), Bioinformatics and Genomic Networks (5 papers), RNA and protein synthesis mechanisms (4 papers), Enzyme Structure and Function (3 papers), Enzyme Production and Characterization (2 papers), Impact of Technology on Adolescents (1 paper) and Chemical Synthesis and Analysis (1 paper). The work is most often cited by research in Computational Theory and Mathematics (217 citations), Molecular Biology (588 citations), Biotechnology (64 citations), Infectious Diseases (74 citations) and Aquatic Science (25 citations). Cunliang Geng has collaborated with scholars based in Netherlands, United States and United Kingdom. Frequent co-authors include Alexandre M. J. J. Bonvin, Li C. Xue, Anna Vangone, Mikaël Trellet, Jörg Schaarschmidt, Panagiotis I. Koukos, Jorge Roel‐Touris, Nicolas Renaud, João Rodrigues and Siddarth Narasimhan. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Bioinformatics, Protein Engineering Design and Selection, Wiley Interdisciplinary Reviews Computational Molecular Science and Biomolecules.

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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