Jun Ding

12.9k citations
194 papers · 5.2k · h-index 42

Impact in

    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies
    • Pluripotent Stem Cells Research
    • Single-cell and spatial transcriptomics
    • MicroRNA in disease regulation

Papers in

    • Single-cell and spatial transcriptomics 22
    • Epigenetics and DNA Methylation 11
    • Machine Learning in Bioinformatics 10
    • Gene Regulatory Network Analysis 10
    • RNA modifications and cancer 10
    • Immune cells in cancer 11

Jun Ding

181 papers receiving 5.1k citations

Peers

Jun Ding
Comparison fields: 5 of 177
  • Molecular Biology 2.6k
  • Cancer Research 444
  • Biomedical Engineering 999
  • Developmental Neuroscience 70
  • Immunology 348
Replace Feng Li with:
Feng Li China
Jian Cheng China
Ping Zhu China
Xiaoyang Wu China
Liu Yang China
Yu‐Chih Chen Taiwan
Danyang Chen China
Giuseppe Maulucci Italy
Yuan Zhang China
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Citations per field
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Citations per year

Countries citing papers authored by Jun Ding

Since Specialization
Citations

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

Fields of papers citing papers by Jun Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 194 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013366
2 2010303
3 2016138
4 2019120
5 2019118
6 2022116
7 2021113
8 200794
9 200189
10 201586
11 201785
12 201480
13 201578
14 201577
15 202076
16 200974
17 201572
18 201571
19 201171
20 201471

About Jun Ding

Jun Ding is a scholar working on Molecular Biology, Immunology, Biomedical Engineering, Cancer Research and Public Health, Environmental and Occupational Health, having authored 194 papers that have together received 5.2k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (22 papers), Epigenetics and DNA Methylation (11 papers), MicroRNA in disease regulation (11 papers), Immune cells in cancer (11 papers), Machine Learning in Bioinformatics (10 papers), Gene Regulatory Network Analysis (10 papers), RNA modifications and cancer (10 papers) and Reproductive Biology and Fertility (10 papers). The work is most often cited by research in Molecular Biology (2.6k citations), Cancer Research (444 citations), Biomedical Engineering (999 citations), Developmental Neuroscience (70 citations) and Immunology (348 citations). Jun Ding has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Yan Xu, Ling‐Yun Wu, Gary D. Smith, Ziv Bar‐Joseph, Kuo‐Chen Chou, Xiaoman Li, Haiyan Hu, Yi Zhang, Zhongjun J. Wu and Zengsheng Chen. Their work appears in journals such as Frontiers in Nutrition, Bioinformatics, Nature Communications, Fertility and Sterility and Biology of Reproduction.

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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