Jun Zou

7.7k citations
53 papers · 1.3k · h-index 20

Impact in

Papers in

Jun Zou

51 papers receiving 1.3k citations

Peers

Jun Zou
Comparison fields: 5 of 139
  • Computational Theory and Mathematics 291
  • Molecular Biology 609
  • Health Information Management 35
  • Horticulture 6
  • Analytical Chemistry 59
Replace Assaf Gottlieb with:
Assaf Gottlieb United States
Anna Bauer‐Mehren United States
Md. Nurul Haque Mollah Bangladesh
Leihong Wu United States
Qingxia Yang China
Marco Masseroli Italy
Scott Boyer Sweden
Heng Luo China
Jun Zou relative to Assaf Gottlieb United States Assaf Gottlieb's profile →
Citations per field
00.5×1.6×
Assaf Gottlieb · 1×
Citations per year

Countries citing papers authored by Jun Zou

Since Specialization
Citations

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

Fields of papers citing papers by Jun Zou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004161
2 201391
3 202283
4 202171
5 202270
6 202266
7 200864
8 201357
9 202147
10 202043
11 201941
12 201240
13 200940
14 202036
15 200935
16 201234
17 202034
18 200823
19 199822
20 201719

About Jun Zou

Jun Zou is a scholar working on Molecular Biology, Computational Theory and Mathematics, Information Systems, Artificial Intelligence and Oncology, having authored 53 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Recommender Systems and Techniques (7 papers), Protein Structure and Dynamics (5 papers), Receptor Mechanisms and Signaling (4 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Spam and Phishing Detection (4 papers), Privacy-Preserving Technologies in Data (4 papers) and Protein Kinase Regulation and GTPase Signaling (3 papers). The work is most often cited by research in Computational Theory and Mathematics (291 citations), Molecular Biology (609 citations), Health Information Management (35 citations), Horticulture (6 citations) and Analytical Chemistry (59 citations). Jun Zou has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Shengyong Yang, Faramarz Fekri, Linli Li, Haixia Qi, Huanzhang Xie, Robert A. Clark, Melvyn S. Tockman, Hong Tang, Michael E. Gruidl and Lihua Li. Their work appears in journals such as European Journal of Medicinal Chemistry, Applied Sciences, Bioorganic & Medicinal Chemistry Letters, Molecular BioSystems and Signal Transduction and Targeted Therapy.

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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