J Ling

53 papers receiving 882 citations

Peers

J Ling
Comparison fields: 5 of 94
  • Molecular Medicine 322
  • Endocrinology 190
  • Applied Microbiology and Biotechnology 42
  • Food Science 346
  • Clinical Biochemistry 89
Replace Fernando Garcı́a-Garrote with:
Fernando Garcı́a-Garrote Spain
Henry Fraimow United States
Shohreh Farshad Iran
Maria Trancassini Italy
Anan Chongthaleong Thailand
V.O. Rotimi Kuwait
K Rahal Algeria
Han Siong Toh Taiwan
Deepthi Nair India
Bülent Sümerkan Türkiye
J Ling relative to Fernando Garcı́a-Garrote Spain Fernando Garcı́a-Garrote's profile →
Citations per field
00.5×1.5×2.1×
Fernando Garcı́a-Garrote · 1×
Citations per year

Countries citing papers authored by J Ling

Since Specialization
Citations

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

Fields of papers citing papers by J Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2003139
2 1990120
3 199081
4 202246
5 199840
6 199936
7 198835
8 198431
9 200030
10 199129
11 200628
12 198821
13 202220
14 198420
15 198118
16 199318
17 200118
18 198218
19
Prevalence of integrons in antibiotic-resistant Salmonella spp. in Hong Kong.
200916
20 202314

About J Ling

J Ling is a scholar working on Molecular Medicine, Food Science, Endocrinology, Molecular Biology and Endocrinology, Diabetes and Metabolism, having authored 57 papers that have together received 969 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (17 papers), Salmonella and Campylobacter epidemiology (15 papers), Vibrio bacteria research studies (5 papers), Diabetes Management and Research (5 papers), Antimicrobial Resistance in Staphylococcus (4 papers), Escherichia coli research studies (4 papers), Bacterial Identification and Susceptibility Testing (4 papers) and Aquaculture disease management and microbiota (4 papers). The work is most often cited by research in Molecular Medicine (322 citations), Endocrinology (190 citations), Applied Microbiology and Biotechnology (42 citations), Food Science (346 citations) and Clinical Biochemistry (89 citations). J Ling has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include A. F. B. Cheng, G.L. French, Edward Wai‐Chi Chan, Yujuan Jin, K M Kam, Thomas K.�W. Ling, P. Y. Chau, S. Donnan, M. Farrington and Juliana C.N. Chan. Their work appears in journals such as Antimicrobial Agents and Chemotherapy, Journal of Antimicrobial Chemotherapy, Journal of Clinical Microbiology, Journal of Clinical Pathology and Epidemiology and Infection.

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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