Daniel Berrar
Impact in
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques
- Machine Learning and Data Classification
Papers in
-
- Bioinformatics and Genomic Networks 7
- Gene expression and cancer classification 5
- Genetics, Bioinformatics, and Biomedical Research 4
- Protein Structure and Dynamics 3
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- Machine Learning and Data Classification 7
- Domain Adaptation and Few-Shot Learning 3
- Co-authors
- Werner Dubitzky (23 shared papers)Peter Flach (1 shared paper)Philippe Lopes (4 shared papers)Ian Bradbury (3 shared papers)C. Stephen Downes (2 shared papers)Alfons Schuster (6 shared papers)Jeyakumar Natarajan (2 shared papers)Catherine Hack (2 shared papers)
- Journals
- Machine Learning (4 papers)BMC Bioinformatics (2 papers)Expert Systems with Applications (2 papers)Journal of Clinical Monitoring and Computing (1 paper)Bioinformatics (1 paper)
- Partner nations
- JapanUnited KingdomGermany
In The Last Decade
Daniel Berrar
48 papers receiving 832 citations
Peers
Comparison fields: 5 of 157
- Artificial Intelligence 258
- Molecular Medicine 34
- Orthopedics and Sports Medicine 44
- Molecular Biology 333
- Health Informatics 6
Countries citing papers authored by Daniel Berrar
This map shows the geographic impact of Daniel Berrar'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 Daniel Berrar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Berrar more than expected).
Fields of papers citing papers by Daniel Berrar
This network shows the impact of papers produced by Daniel Berrar. 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 Daniel Berrar. The network helps show where Daniel Berrar may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Berrar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 96 | |
| 2 | 2010 | 81 | |
| 3 | 2006 | 54 | |
| 4 | 2002 | 52 | |
| 5 | 2018 | 52 | |
| 6 | Detecting click fraud in online advertising: a data mining approach | 2014 | 45 |
| 7 | 2006 | 43 | |
| 8 | 2019 | 36 | |
| 9 | Proceedings of 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2014) | 2014 | 34 |
| 10 | 2001 | 28 | |
| 11 | 2018 | 27 | |
| 12 | 2011 | 25 | |
| 13 | 2008 | 24 | |
| 14 | 2005 | 23 | |
| 15 | 2009 | 22 | |
| 16 | 2005 | 21 | |
| 17 | 2021 | 19 | |
| 18 | 2012 | 19 | |
| 19 | 2006 | 18 | |
| 20 | 2016 | 18 |
About Daniel Berrar
Daniel Berrar is a scholar working on Molecular Biology, Artificial Intelligence, Economics and Econometrics, Computer Vision and Pattern Recognition and Genetics, having authored 48 papers that have together received 866 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (7 papers), Bioinformatics and Genomic Networks (7 papers), Sports Analytics and Performance (5 papers), Gene expression and cancer classification (5 papers), Genetics, Bioinformatics, and Biomedical Research (4 papers), Advanced Statistical Methods and Models (3 papers), Protein Structure and Dynamics (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Artificial Intelligence (258 citations), Molecular Medicine (34 citations), Orthopedics and Sports Medicine (44 citations), Molecular Biology (333 citations) and Health Informatics (6 citations). Daniel Berrar has collaborated with scholars based in Japan, United Kingdom and Germany. Frequent co-authors include Werner Dubitzky, Peter Flach, Philippe Lopes, Ian Bradbury, C. Stephen Downes, Alfons Schuster, Jeyakumar Natarajan, Catherine Hack, Elena Deligianni and Nigel G. Ternan. Their work appears in journals such as Machine Learning, BMC Bioinformatics, Expert Systems with Applications, Journal of Clinical Monitoring and Computing and Bioinformatics.
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.