Hung-Mo Chen

22 papers receiving 433 citations

Peers

Hung-Mo Chen
Comparison fields: 5 of 40
  • Molecular Medicine 136
  • Clinical Biochemistry 74
  • Endocrinology 50
  • Food Science 77
  • Microbiology 18
Replace Lipika Singhal with:
Lipika Singhal India
Hassan Namdari United States
Emily B. Jacobs United States
Neil Doherty United Kingdom
Balvinder Mohan India
Ana Fernández-Olmos Spain
Holly Ciesielczuk United Kingdom
Nelson P. Moyer United States
Leonard Schuele Netherlands
Gioconda Brigante Italy
Hung-Mo Chen relative to Lipika Singhal India Lipika Singhal's profile →
Citations per field
00.5×2×2.6×
Lipika Singhal · 1×
Citations per year

Countries citing papers authored by Hung-Mo Chen

Since Specialization
Citations

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

Fields of papers citing papers by Hung-Mo Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hung-Mo Chen. 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 Hung-Mo Chen. The network helps show where Hung-Mo Chen may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Arcobacter butzleri bacteremia in a patient with liver cirrhosis.
200069
2 200649
3 201247
4 201444
5 201131
6 200727
7 200726
8 200621
9 201217
10 200716
11 201016
12 201115
13 200514
14
Comparison of CPS ID 3 and CHROMagar Orientation chromogenic agars with standard biplate technique for culture of clinical urine samples.
200814
15 201314
16 201013
17 20078
18 20135
19
Detection of Mycobacterium tuberculosis Complex in Paraffin-Embedded Tissues by the New Automated Abbott RealTime MTB Assay.
20165
20 20185

About Hung-Mo Chen

Hung-Mo Chen is a scholar working on Clinical Biochemistry, Molecular Medicine, Infectious Diseases, Endocrinology and Food Science, having authored 22 papers that have together received 459 indexed citations. Recurring topics across this work include Bacterial Identification and Susceptibility Testing (6 papers), Antibiotic Resistance in Bacteria (6 papers), Salmonella and Campylobacter epidemiology (3 papers), Tuberculosis Research and Epidemiology (2 papers), Infections and bacterial resistance (2 papers), Fungal Infections and Studies (2 papers), Vibrio bacteria research studies (2 papers) and Antifungal resistance and susceptibility (1 paper). The work is most often cited by research in Molecular Medicine (136 citations), Clinical Biochemistry (74 citations), Endocrinology (50 citations), Food Science (77 citations) and Microbiology (18 citations). Hung-Mo Chen has collaborated with scholars based in Taiwan, Belgium and China. Frequent co-authors include Wen‐Chien Ko, Jing-Jou Yan, Jiunn-Jong Wu, Jiunn-Jong Wu, Tsung Chain Chang, Ay‐Huey Huang, Jing Yan, Po‐Lin Chen, Ying Jin and Lee‐Jene Teng. Their work appears in journals such as Diagnostic Microbiology and Infectious Disease, Journal of Microbiology Immunology and Infection, Journal of Clinical Microbiology, Frontiers in Microbiology and Journal of Medical Microbiology.

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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