J U Que

1.3k citations
28 papers · 1.1k · h-index 19

Impact in

Papers in

J U Que

26 papers receiving 976 citations

Peers

J U Que
Comparison fields: 5 of 64
  • Endocrinology 132
  • Microbiology 181
  • Immunology 152
  • Molecular Medicine 41
  • Applied Microbiology and Biotechnology 14
Replace Danka Pavliakova with:
Danka Pavliakova United States
Éric Abachin France
F. Chiarini Italy
Steven M. Callister United States
Paula A. Revell United States
Diane Dryja United States
Dwight W. Lambe United States
Cédric Badiou France
Christina von Hunolstein Italy
Paul B. Keiser United States
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Citations per field
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Danka Pavliakova · 1×
Citations per year

Countries citing papers authored by J U Que

Since Specialization
Citations

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

Fields of papers citing papers by J U Que

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1994176
2 1985121
3 198597
4 198694
5 199175
6 199247
7 199145
8 199241
9
Immunization of cystic fibrosis patients with a Pseudomonas aeruginosa O-polysaccharide-toxin A conjugate vaccine.
199741
10 199439
11 199138
12 199435
13 199535
14 198733
15 199030
16 199629
17 199126
18 199626
19
Elevated levels of maternal anti-tetanus toxin antibodies do not suppress the immune response to a Haemophilus influenzae type b polyribosylphosphate-tetanus toxoid conjugate vaccine.
200021
20 200019

About J U Que

J U Que is a scholar working on Microbiology, Endocrinology, Virology, Molecular Biology and Food Science, having authored 28 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bacterial Infections and Vaccines (9 papers), Bacterial biofilms and quorum sensing (5 papers), Gut microbiota and health (5 papers), Malaria Research and Control (4 papers), Cystic Fibrosis Research Advances (4 papers), Salmonella and Campylobacter epidemiology (3 papers), Vibrio bacteria research studies (3 papers) and HIV Research and Treatment (2 papers). The work is most often cited by research in Endocrinology (132 citations), Microbiology (181 citations), Immunology (152 citations), Molecular Medicine (41 citations) and Applied Microbiology and Biotechnology (14 citations). J U Que has collaborated with scholars based in United States, Switzerland and Thailand. Frequent co-authors include Stanley J. Cryz, D. J. Hentges, E Fürer, Aloïs B. Lang, B Scarpa, Robert Mischler, Reinhard Glück, U. B. Schaad, Joanna Wedgwood and Anna Rüdeberg. Their work appears in journals such as Infection and Immunity, Vaccine, The Journal of Infectious Diseases, The Lancet and Blood.

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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