Matilda Berkell

445 citations
9 papers · 67 · h-index 4

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 4
    • COVID-19 Clinical Research Studies 3
    • SARS-CoV-2 detection and testing 2
    • Antimicrobial Resistance in Staphylococcus 1
    • Bacterial biofilms and quorum sensing 2
    • Gut microbiota and health 2

Matilda Berkell

9 papers receiving 67 citations

Peers

Matilda Berkell
Comparison fields: 5 of 38
  • Infectious Diseases 38
  • Biological Psychiatry 4
  • Molecular Medicine 5
  • Molecular Biology 40
  • Animal Science and Zoology 5
Replace Kévin Da Silva with:
Kévin Da Silva France
Alessandra Guarnaccia Italy
Samantha Hao United States
Ivan Topolsky Switzerland
Evgenii I. Olekhnovich Russia
Paul B. Stege Netherlands
Xu Jianqing China
Massimo Francalancia Italy
Josh Quick United Kingdom
Bremy Alburquerque United States
Matilda Berkell relative to Kévin Da Silva France Kévin Da Silva's profile →
Citations per field
00.5×1.5×2.2×
Kévin Da Silva · 1×
Citations per year

Countries citing papers authored by Matilda Berkell

Since Specialization
Citations

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

Fields of papers citing papers by Matilda Berkell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 202324
2 202214
3 202212
4 20214
5 20213
6 20223
7 20243
8 20242
9 20222

About Matilda Berkell

Matilda Berkell is a scholar working on Infectious Diseases, Molecular Biology, Molecular Medicine, Critical Care and Intensive Care Medicine and Pollution, having authored 9 papers that have together received 67 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (4 papers), COVID-19 Clinical Research Studies (3 papers), Bacterial biofilms and quorum sensing (2 papers), SARS-CoV-2 detection and testing (2 papers), Gut microbiota and health (2 papers), Antibiotic Resistance in Bacteria (2 papers), Animal Nutrition and Physiology (1 paper) and Antimicrobial Resistance in Staphylococcus (1 paper). The work is most often cited by research in Infectious Diseases (38 citations), Biological Psychiatry (4 citations), Molecular Medicine (5 citations), Molecular Biology (40 citations) and Animal Science and Zoology (5 citations). Matilda Berkell has collaborated with scholars based in Belgium, Italy and United Kingdom. Frequent co-authors include Surbhi Malhotra‐Kumar, Samir Kumar‐Singh, An Hotterbeekx, Herman Goossens, Basil Britto Xavier, Evelina Tacconelli, Elisa Danese, Alessia Savoldi, Akshita Gupta and Pasquale De Nardo. Their work appears in journals such as Eurosurveillance, Antimicrobial Resistance and Infection Control, Frontiers in Immunology, mSystems and Journal of Medical Virology.

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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