Infection, Anti-microbiens, Modélisation, Evolution
Impact in
- Molecular Medicine top 2%
- Antibiotic Resistance in Bacteria
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- Antibiotic Use and Resistance
Papers in
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- Antibiotic Resistance in Bacteria 269
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- Antibiotic Use and Resistance 72
- Top scholars
- Jean‐François TimsitÉrick DenamurOlivier TenaillonPatrice NordmannLaurent PoirelNathan Peiffer‐SmadjaOlivier ClermontFrance Mentré
- Journals
- Journal of Antimicrobial Chemotherapy (107 papers)Clinical Microbiology and Infection (87 papers)PLoS ONE (71 papers)Antimicrobial Agents and Chemotherapy (71 papers)Intensive Care Medicine (65 papers)
- Partner nations
- FranceUnited StatesSwitzerland
In The Last Decade
Infection, Anti-microbiens, Modélisation, Evolution
1.7k papers receiving 35.2k citations
Peers
Comparison fields: 5 of 214
- Molecular Medicine 6.8k
- Applied Microbiology and Biotechnology 2.2k
- Endocrinology 3.4k
- Critical Care and Intensive Care Medicine 2.5k
- Infectious Diseases 9.8k
Countries citing scholars working at Infection, Anti-microbiens, Modélisation, Evolution
This map shows the geographic impact of research produced by authors working at Infection, Anti-microbiens, Modélisation, Evolution. 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 papers produced at Infection, Anti-microbiens, Modélisation, Evolution with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Infection, Anti-microbiens, Modélisation, Evolution more than expected).
Fields of papers published by authors at Infection, Anti-microbiens, Modélisation, Evolution
This network shows the impact of papers affiliated with Infection, Anti-microbiens, Modélisation, Evolution at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Infection, Anti-microbiens, Modélisation, Evolution at the time of their publication.
About Infection, Anti-microbiens, Modélisation, Evolution
In recent decades, authors affiliated with Infection, Anti-microbiens, Modélisation, Evolution have published 2.1k papers, which have received a total of 44.2k indexed citations . Scholars at this organization have produced 269 papers in Molecular Medicine, 72 papers in Applied Microbiology and Biotechnology, 526 papers in Infectious Diseases, 152 papers in Endocrinology and 87 papers in Critical Care and Intensive Care Medicine on the topics of Antibiotic Resistance in Bacteria (269 papers), HIV/AIDS drug development and treatment (116 papers), Antibiotics Pharmacokinetics and Efficacy (87 papers), Escherichia coli research studies (84 papers), Bacterial Identification and Susceptibility Testing (76 papers), Pneumonia and Respiratory Infections (75 papers), Antibiotic Use and Resistance (72 papers) and HIV Research and Treatment (72 papers). Their work is cited by papers focused on Molecular Medicine (6.8k citations), Applied Microbiology and Biotechnology (2.2k citations), Endocrinology (3.4k citations), Critical Care and Intensive Care Medicine (2.5k citations) and Infectious Diseases (9.8k citations). Authors at Infection, Anti-microbiens, Modélisation, Evolution collaborate with scholars in France, United States and Switzerland and have published in prestigious journals including Journal of Antimicrobial Chemotherapy, Clinical Microbiology and Infection, PLoS ONE, Antimicrobial Agents and Chemotherapy and Intensive Care Medicine. Some of Infection, Anti-microbiens, Modélisation, Evolution's most productive authors include Jean‐François Timsit, Érick Denamur, Olivier Tenaillon, Patrice Nordmann, Laurent Poirel, Nathan Peiffer‐Smadja, Olivier Clermont, France Mentré, Yazdan Yazdanpanah and Jean-Damien Ricard.
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.