Zhongcheng Cao

871 citations
27 papers · 719 indexed · h-index 17
Topics
Cholinesterase and Neurodegenerative Diseases (24 papers)Computational Drug Discovery Methods (16 papers)Alzheimer's disease research and treatments (12 papers)
Partner nations
ChinaUnited States

In The Last Decade

Zhongcheng Cao

27 papers receiving 715 citations

Peers

Zhongcheng Cao
Comparison fields: 5 of 66
  • Pharmacology 486
  • Computational Theory and Mathematics 320
  • Organic Chemistry 299
  • Physiology 221
  • Molecular Biology 133
Replace Xiaoming Qiang with:
Xiaoming Qiang China
Qing Song China
Tarek Mohamed Canada
Vendula Šepsová Czechia
Lintao Yu China
Jakub Jończyk Poland
Pavan Srivastava India
Kelvin D.G. Wang China
Gerard Esteban Spain
Zonghua Luo United States
Zhongcheng Cao relative to Xiaoming Qiang China Xiaoming Qiang's profile →
Citations per field
00.5×1.5×
Xiaoming Qiang · 1×
Citations per year

Countries citing papers authored by Zhongcheng Cao

Since Specialization
Citations

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

Fields of papers citing papers by Zhongcheng Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhongcheng Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Zhongcheng Cao. A scholar is included among the top collaborators of Zhongcheng Cao 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 Zhongcheng Cao. Zhongcheng Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 5
4 33
5 16
6 31
7 19
8 37
9 43
10 52
11 24
12 54
13 13
14 67
15 29
16 33
17 26
18 81
19 57
20 2

About Zhongcheng Cao

Zhongcheng Cao is a scholar working on Pharmacology, Computational Theory and Mathematics and Complementary and alternative medicine, having authored 27 papers that have together received 719 indexed citations. Recurring topics across this work include Cholinesterase and Neurodegenerative Diseases (24 papers), Computational Drug Discovery Methods (16 papers) and Alzheimer's disease research and treatments (12 papers). The work is most often cited by research in Pharmacology (486 citations), Computational Theory and Mathematics (320 citations) and Complementary and alternative medicine (86 citations). Zhongcheng Cao has collaborated with scholars based in China and United States. Frequent co-authors include Yong Deng, Xiaoming Qiang, Qing Song, Zhenghuai Tan, Yan Li, Li Luo, Rui Xu, Yang Xia, Ganyuan Xiao and Li Zhang. Their work appears in journals such as European Journal of Medicinal Chemistry, Current Medicinal Chemistry and Bioorganic & Medicinal 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.

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