Pingjian Ding

1.6k citations
58 papers · 1.2k · h-index 19

Impact in

Papers in

    • Bioinformatics and Genomic Networks 18
    • RNA modifications and cancer 13
    • Machine Learning in Bioinformatics 11
    • Circular RNAs in diseases 11
    • Biomedical Text Mining and Ontologies 5
    • Cancer-related molecular mechanisms research 25
    • MicroRNA in disease regulation 22

Pingjian Ding

53 papers receiving 1.2k citations

Peers

Pingjian Ding
Comparison fields: 5 of 92
  • Cancer Research 703
  • Computational Theory and Mathematics 227
  • Molecular Biology 984
  • Computational Mathematics 8
  • Health Information Management 17
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Citations per field
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Citations per year

Countries citing papers authored by Pingjian Ding

Since Specialization
Citations

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

Fields of papers citing papers by Pingjian Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017210
2 201665
3 201864
4 201757
5 201853
6 201750
7 202249
8 201945
9 201944
10 201843
11 202037
12 201829
13 201826
14 201625
15 201822
16 201822
17 202019
18 201818
19 201918
20 202017

About Pingjian Ding

Pingjian Ding is a scholar working on Molecular Biology, Cancer Research, Computational Theory and Mathematics, Genetics and Pharmacology, having authored 58 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (25 papers), MicroRNA in disease regulation (22 papers), Computational Drug Discovery Methods (19 papers), Bioinformatics and Genomic Networks (18 papers), RNA modifications and cancer (13 papers), Machine Learning in Bioinformatics (11 papers), Circular RNAs in diseases (11 papers) and Biomedical Text Mining and Ontologies (5 papers). The work is most often cited by research in Cancer Research (703 citations), Computational Theory and Mathematics (227 citations), Molecular Biology (984 citations), Computational Mathematics (8 citations) and Health Information Management (17 citations). Pingjian Ding has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Jiawei Luo, Cheng Liang, Qiu Xiao, Guanghui Li, Jie Cai, Xiangtao Chen, Rong Xu, Cong Shen, Jiawei Luo and Rui Yin. Their work appears in journals such as Journal of Biomedical Informatics, IEEE Journal of Biomedical and Health Informatics, IEEE Access, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Journal of Chemical Information and Modeling.

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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