Matilda Berkell

465 citations
11 papers · 74 · h-index 5

Impact in

Papers in

    • SARS-CoV-2 and COVID-19 Research 5
    • COVID-19 Clinical Research Studies 3
    • SARS-CoV-2 detection and testing 2
    • Gut microbiota and health 2
    • Bacterial biofilms and quorum sensing 1

Matilda Berkell

9 papers receiving 74 citations

Peers

Matilda Berkell
Comparison fields: 5 of 37
  • Infectious Diseases 35
  • Biological Psychiatry 4
  • Molecular Medicine 4
  • Molecular Biology 36
  • Complementary and Manual Therapy 1
Replace Kévin Da Silva with:
Kévin Da Silva France
Sudeep Mehrotra United States
Samantha Hao United States
Beathe Kiland Granerud Norway
Evgenii I. Olekhnovich Russia
Hanne Søyland Norway
Levy A. Sominsky United States
Massimo Francalancia Italy
Ivan Topolsky Switzerland
Josh Quick United Kingdom
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Citations per field
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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

11 of 11 papers shown
#Work
1 202325
2 202215
3 202212
4 20215
5 20245
6 20244
7 20223
8 20213
9 20222
10 20250
11 20250

About Matilda Berkell

Matilda Berkell is a scholar working on Infectious Diseases, Molecular Biology, Critical Care and Intensive Care Medicine, Pollution and Animal Science and Zoology, having authored 11 papers that have together received 74 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), COVID-19 Clinical Research Studies (3 papers), SARS-CoV-2 detection and testing (2 papers), Gut microbiota and health (2 papers), Animal Nutrition and Physiology (1 paper), Neonatal and Maternal Infections (1 paper), Bacterial biofilms and quorum sensing (1 paper) and Respiratory viral infections research (1 paper). The work is most often cited by research in Infectious Diseases (35 citations), Biological Psychiatry (4 citations), Molecular Medicine (4 citations), Molecular Biology (36 citations) and Complementary and Manual Therapy (1 citation). Matilda Berkell has collaborated with scholars based in Belgium, Italy and Uganda. Frequent co-authors include Surbhi Malhotra‐Kumar, Samir Kumar‐Singh, Basil Britto Xavier, An Hotterbeekx, Herman Goossens, Evelina Tacconelli, Elda Righi, Alessia Savoldi, Pasquale De Nardo and Mohamed Mysara. Their work appears in journals such as Eurosurveillance, Virology, Journal of Medical Virology, Frontiers in Immunology and Journal of Clinical Investigation.

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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