Che Zhang

1.2k citations
35 papers · 788 · h-index 14

Impact in

Papers in

Che Zhang

32 papers receiving 769 citations

Peers

Che Zhang
Comparison fields: 5 of 107
  • Genetics 129
  • Transplantation 12
  • Pharmacology 41
  • Developmental Neuroscience 16
  • Molecular Biology 272
Replace John S. Grundy with:
John S. Grundy United States
Andreas Baumann Germany
Rebecca B. Klisovic United States
Li Zhu China
Lijuan Wen China
Stefania Napolitano Italy
Zhihua Ruan China
Pu Chen China
Steven V. Molinski Canada
Che Zhang relative to John S. Grundy United States John S. Grundy's profile →
Citations per field
00.5×
John S. Grundy · 1×
Citations per year

Countries citing papers authored by Che Zhang

Since Specialization
Citations

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

Fields of papers citing papers by Che Zhang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019107
2 201888
3 200584
4 202083
5 202068
6 202167
7 201953
8 202248
9 202430
10 200828
11 200827
12 202118
13 200815
14 202314
15 201513
16 20097
17 20246
18
An Innovation of Estimating Value at Risk of International Carbon Market:Conditional Autoregressive Value at Risk Models with Refinements from Extreme Value Theory
20154
19 19984
20 20253

About Che Zhang

Che Zhang is a scholar working on Molecular Biology, Organic Chemistry, Immunology, Plant Science and Nephrology, having authored 35 papers that have together received 788 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (5 papers), Carbohydrate Chemistry and Synthesis (4 papers), Galectins and Cancer Biology (3 papers), Mesenchymal stem cell research (2 papers), Chromosomal and Genetic Variations (2 papers), Cerebral Palsy and Movement Disorders (2 papers), Parathyroid Disorders and Treatments (2 papers) and Ubiquitin and proteasome pathways (1 paper). The work is most often cited by research in Genetics (129 citations), Transplantation (12 citations), Pharmacology (41 citations), Developmental Neuroscience (16 citations) and Molecular Biology (272 citations). Che Zhang has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Li Huang, Xihui Zhou, Jiaowei Gu, Xing Chen, Bo Cheng, Qi Tang, Xin Wang, Ke Qin, Haixia Lü and Zhujun Shen. Their work appears in journals such as Stem Cell Research & Therapy, Global Pediatric Health, BMJ Open, Bioorganic & Medicinal Chemistry and Biomaterials Science.

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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