Jean-Paul Ebejer

21 papers receiving 495 citations

Peers

Jean-Paul Ebejer
Comparison fields: 5 of 99
  • Computational Theory and Mathematics 200
  • Health Informatics 5
  • Molecular Medicine 17
  • Molecular Biology 210
  • Pharmacology 37
Replace Eduardo Habib Bechelane Maia with:
Eduardo Habib Bechelane Maia Brazil
Gopalakrishnan Bulusu India
Michiel Vanmeert Belgium
Rajendra Bhadane Finland
Martin Nervall Sweden
Shuo Zhang China
Indira Ghosh India
Amr Alhossary Singapore
Atefeh Saadabadi Finland
Emily Chen United States
Jean-Paul Ebejer relative to Eduardo Habib Bechelane Maia Brazil Eduardo Habib Bechelane Maia's profile →
Citations per field
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Eduardo Habib Bechelane Maia · 1×
Citations per year

Countries citing papers authored by Jean-Paul Ebejer

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Paul Ebejer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Paul Ebejer. 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 Jean-Paul Ebejer. The network helps show where Jean-Paul Ebejer may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012176
2 201963
3 201247
4 201647
5 202236
6 201334
7 201329
8 202018
9 201410
10 20199
11 20138
12 20146
13 20216
14 20185
15 20223
16 20223
17 20212
18 20172
19 20241
20 20211

About Jean-Paul Ebejer

Jean-Paul Ebejer is a scholar working on Molecular Biology, Computational Theory and Mathematics, Information Systems, Materials Chemistry and Public Health, Environmental and Occupational Health, having authored 22 papers that have together received 507 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), Protein Structure and Dynamics (4 papers), Metabolomics and Mass Spectrometry Studies (3 papers), Machine Learning in Materials Science (3 papers), Malaria Research and Control (2 papers), Software Engineering Research (2 papers), Advanced Software Engineering Methodologies (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Computational Theory and Mathematics (200 citations), Health Informatics (5 citations), Molecular Medicine (17 citations), Molecular Biology (210 citations) and Pharmacology (37 citations). Jean-Paul Ebejer has collaborated with scholars based in Malta, United Kingdom and China. Frequent co-authors include Charlotte M. Deane, Garrett M. Morris, Paul W. Finn, M. Charlton, Simone Fulle, Gillian M. Martin, Jiye Shi, Sebastian Kelm, Michael J. Blackman and Maria Penzo. Their work appears in journals such as Journal of Chemical Information and Modeling, Frontiers in Pharmacology, International Journal of Molecular Sciences, European Journal of Human Genetics and Journal of Cheminformatics.

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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