L.‐K. Ng

36 papers receiving 1.6k citations

L.‐K. Ng's Hit Papers

Multiplex PCR for the detection of tetracycline resistant genes 2001 · 743 citations
7430+8+16Years since publication200400600

Peers

L.‐K. Ng
Comparison fields: 5 of 87
  • Molecular Medicine 439
  • Endocrinology 226
  • Food Science 752
  • Biotechnology 284
  • Pollution 380
Replace Linda English with:
Linda English United States
Hyang-Mi Nam South Korea
Cesar A. Morales United States
Karin Schwaiger Germany
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Teresa M. Barbosa Ireland
Marisa Ribeiro de Itapema Cardoso Brazil
Ashish A. Sawant United States
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Citations per field
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Citations per year

Countries citing papers authored by L.‐K. Ng

Since Specialization
Citations

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

Fields of papers citing papers by L.‐K. Ng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L.‐K. Ng. 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 L.‐K. Ng. The network helps show where L.‐K. Ng may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Multiplex PCR for the detection of tetracycline resistant genes
Hit paper breakdown →
2001743
2 201382
3 198577
4 198556
5 199754
6 200652
7 199752
8 200949
9 198547
10 200746
11 198144
12 198136
13 198836
14 201129
15 200921
16 199420
17 199520
18 197820
19 199320
20 200919

About L.‐K. Ng

L.‐K. Ng is a scholar working on Food Science, Molecular Medicine, Biotechnology, Microbiology and Clinical Biochemistry, having authored 37 papers that have together received 1.7k indexed citations. Recurring topics across this work include Salmonella and Campylobacter epidemiology (16 papers), Antibiotic Resistance in Bacteria (7 papers), Food Safety and Hygiene (7 papers), Bacteriophages and microbial interactions (7 papers), Bacterial Identification and Susceptibility Testing (6 papers), Listeria monocytogenes in Food Safety (6 papers), Reproductive tract infections research (5 papers) and Antimicrobial Resistance in Staphylococcus (4 papers). The work is most often cited by research in Molecular Medicine (439 citations), Endocrinology (226 citations), Food Science (752 citations), Biotechnology (284 citations) and Pollution (380 citations). L.‐K. Ng has collaborated with scholars based in Canada, United States and China. Frequent co-authors include M. R. Mulvey, Michelle J. Alfa, Irene Etayo Martín, Michael E. Stiles, Diane Taylor, Jeff Farber, Celine A. Nadon, Richard K. Sherburne, Hermy Lior and Jo‐Anne R. Dillon. Their work appears in journals such as Journal of Clinical Microbiology, Applied and Environmental Microbiology, Journal of Food Protection, Epidemiology and Infection and Antimicrobial Agents and Chemotherapy.

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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