Dan Yan

1.4k citations
34 papers · 1.0k · h-index 15

Impact in

Papers in

    • Gut microbiota and health 9
    • Metabolomics and Mass Spectrometry Studies 3
    • Metabolism, Diabetes, and Cancer 2
    • Clostridium difficile and Clostridium perfringens research 3

Dan Yan

33 papers receiving 1.0k citations

Peers

Dan Yan
Comparison fields: 5 of 118
  • Health Information Management 48
  • Pollution 89
  • Animal Science and Zoology 67
  • Molecular Biology 386
  • Pharmacology 40
Replace Tarun Kumar Upadhyay with:
Tarun Kumar Upadhyay India
Xiaoya Wang China
Tian Tang China
Uzma Azeem Awan Pakistan
Reza Hajihosseini Iran
Xue Shen China
Xiaozhen Guo China
Dipta Dey Bangladesh
Yinsheng Qiu China
Ahmad Firoz Saudi Arabia
Dan Yan relative to Tarun Kumar Upadhyay India Tarun Kumar Upadhyay's profile →
Citations per field
00.5×6.1×
Tarun Kumar Upadhyay · 1×
Citations per year

Countries citing papers authored by Dan Yan

Since Specialization
Citations

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

Fields of papers citing papers by Dan Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021163
2 2021145
3 2022102
4 201980
5 201974
6 202168
7 202263
8 202346
9 201844
10 202336
11 202431
12 202120
13 202319
14 202317
15 202116
16 202413
17 202413
18 202112
19 202412
20 20249

About Dan Yan

Dan Yan is a scholar working on Molecular Biology, Infectious Diseases, Complementary and alternative medicine, Endocrinology, Diabetes and Metabolism and Physiology, having authored 34 papers that have together received 1.0k indexed citations. Recurring topics across this work include Gut microbiota and health (9 papers), Diet and metabolism studies (3 papers), Clostridium difficile and Clostridium perfringens research (3 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Healthcare (2 papers), Metabolism, Diabetes, and Cancer (2 papers) and Artificial Intelligence in Healthcare (2 papers). The work is most often cited by research in Health Information Management (48 citations), Pollution (89 citations), Animal Science and Zoology (67 citations), Molecular Biology (386 citations) and Pharmacology (40 citations). Dan Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Kejun Deng, Ruizheng Liang, Tingting Hu, Zhengdi Wang, Min Wei, Weicheng Shen, Hua Tang, Hui Yang, Hao Lin and Yamei Luo. Their work appears in journals such as Microchemical Journal, ACS Omega, Journal of Pharmacy & Pharmaceutical Sciences, Frontiers in Microbiology and The Journal of Infectious Diseases.

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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