Hang Pan

1.8k citations
35 papers · 1.4k · h-index 22

Impact in

Papers in

Hang Pan

34 papers receiving 1.3k citations

Peers

Hang Pan
Comparison fields: 5 of 94
  • Molecular Medicine 561
  • Endocrinology 353
  • Food Science 847
  • Biotechnology 181
  • Pollution 206
Replace Maria Hoffmann with:
Maria Hoffmann United States
Dayna M. Harhay United States
Dália dos Prazeres Rodrigues Brazil
Oksana Lukjančenko Denmark
Bhoj Raj Singh India
Atsushi Hinenoya Japan
Jie Zheng United States
Sophie Mangenot France
Ammini Parvathi India
Maria Helena Matté Brazil
Hang Pan relative to Maria Hoffmann United States Maria Hoffmann's profile →
Citations per field
00.5×1.5×1.9×
Maria Hoffmann · 1×
Citations per year

Countries citing papers authored by Hang Pan

Since Specialization
Citations

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

Fields of papers citing papers by Hang Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hang Pan, 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 Hang Pan Line = papers co-authored together Hang Pan 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 2019200
2 2019191
3 2018125
4 201864
5 202250
6 201947
7 201847
8 202047
9 202047
10 202047
11 202045
12 201945
13 202138
14 202236
15 201836
16 202034
17 202032
18 201828
19 202128
20 202228

About Hang Pan

Hang Pan is a scholar working on Food Science, Molecular Medicine, Endocrinology, Global and Planetary Change and Molecular Biology, having authored 35 papers that have together received 1.4k indexed citations. Recurring topics across this work include Salmonella and Campylobacter epidemiology (18 papers), Antibiotic Resistance in Bacteria (15 papers), Vibrio bacteria research studies (9 papers), Pharmaceutical and Antibiotic Environmental Impacts (4 papers), Aquaculture disease management and microbiota (3 papers), Climate variability and models (3 papers), Hydrology and Watershed Management Studies (3 papers) and Plant-Microbe Interactions and Immunity (2 papers). The work is most often cited by research in Molecular Medicine (561 citations), Endocrinology (353 citations), Food Science (847 citations), Biotechnology (181 citations) and Pollution (206 citations). Hang Pan has collaborated with scholars based in China, Nepal and United States. Frequent co-authors include Min Yue, Narayan Paudyal, Weihuan Fang, Silpak Biswas, Mohammed Elbediwi, Weihuan Fang, Yan Li, Xiaoliang Li, Xuchu Wang and Beibei Wu. Their work appears in journals such as Frontiers in Microbiology, PeerJ, Frontiers in Veterinary Science, International Journal of Food Microbiology and Frontiers in Bioengineering and Biotechnology.

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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