Daniel Berrar
Impact in
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques
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- Gene expression and cancer classification
- Bioinformatics and Genomic Networks
- Biomedical Text Mining and Ontologies
- Bacterial biofilms and quorum sensing
Papers in
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- Machine Learning and Data Classification 7
- Imbalanced Data Classification Techniques 4
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- Gene expression and cancer classification 11
- Bioinformatics and Genomic Networks 8
- Machine Learning in Bioinformatics 4
- Genetics, Bioinformatics, and Biomedical Research 4
- Co-authors
- Werner Dubitzky (24 shared papers)Peter A. Flach (1 shared paper)C. Stephen Downes (4 shared papers)Martin Granzow (6 shared papers)Philippe Lopes (4 shared papers)Ian Bradbury (4 shared papers)Alfons Schuster (6 shared papers)Catherine Jane Hack (2 shared papers)
- Journals
- Machine Learning (4 papers)Briefings in Bioinformatics (2 papers)BMC Bioinformatics (2 papers)Expert Systems with Applications (2 papers)Bioinformatics (1 paper)
- Partner nations
- JapanUnited KingdomGermany
In The Last Decade
Daniel Berrar
49 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 155
- Artificial Intelligence 313
- Molecular Biology 425
- Orthopedics and Sports Medicine 49
- Molecular Medicine 30
- Information Systems 110
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 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 111 | |
| 2 | 2010 | 85 | |
| 3 | 2005 | 76 | |
| 4 | 2006 | 60 | |
| 5 | 2018 | 58 | |
| 6 | Detecting click fraud in online advertising: a data mining approach | 2014 | 58 |
| 7 | 2002 | 57 | |
| 8 | 2006 | 50 | |
| 9 | 2019 | 39 | |
| 10 | 2018 | 38 | |
| 11 | 2021 | 37 | |
| 12 | 2001 | 32 | |
| 13 | 2008 | 28 | |
| 14 | 2005 | 28 | |
| 15 | 2005 | 26 | |
| 16 | 2011 | 25 | |
| 17 | 2009 | 23 | |
| 18 | 2021 | 21 | |
| 19 | 2015 | 20 | |
| 20 | 2012 | 20 |
About Daniel Berrar
Daniel Berrar is a scholar working on Artificial Intelligence, Molecular Biology, Statistics and Probability, Biophysics and Computer Vision and Pattern Recognition, having authored 49 papers that have together received 1.1k indexed citations. Recurring topics across this work include Gene expression and cancer classification (11 papers), Bioinformatics and Genomic Networks (8 papers), Machine Learning and Data Classification (7 papers), Sports Analytics and Performance (4 papers), Imbalanced Data Classification Techniques (4 papers), Machine Learning in Bioinformatics (4 papers), Advanced Statistical Methods and Models (4 papers) and Genetics, Bioinformatics, and Biomedical Research (4 papers). The work is most often cited by research in Artificial Intelligence (313 citations), Molecular Biology (425 citations), Orthopedics and Sports Medicine (49 citations), Molecular Medicine (30 citations) and Information Systems (110 citations). Daniel Berrar has collaborated with scholars based in Japan, United Kingdom and Germany. Frequent co-authors include Werner Dubitzky, Peter A. Flach, C. Stephen Downes, Martin Granzow, Philippe Lopes, Ian Bradbury, Alfons Schuster, Catherine Jane Hack, Jeyakumar Natarajan and J. Stuart Elborn. Their work appears in journals such as Machine Learning, Briefings in Bioinformatics, BMC Bioinformatics, Expert Systems with Applications 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.