Daniel Berrar

3.4k total citations
48 papers, 866 citations indexed

About

Daniel Berrar is a scholar working on Molecular Biology, Artificial Intelligence and Economics and Econometrics. According to data from OpenAlex, Daniel Berrar has authored 48 papers receiving a total of 866 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 17 papers in Artificial Intelligence and 5 papers in Economics and Econometrics. Recurrent topics in Daniel Berrar's work include Bioinformatics and Genomic Networks (7 papers), Machine Learning and Data Classification (7 papers) and Gene expression and cancer classification (5 papers). Daniel Berrar is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Machine Learning and Data Classification (7 papers) and Gene expression and cancer classification (5 papers). Daniel Berrar collaborates with scholars based in Japan, United Kingdom and Germany. Daniel Berrar's co-authors include Werner Dubitzky, Peter Flach, Philippe Lopes, Ian Bradbury, C. Stephen Downes, Alfons Schuster, Catherine Hack, Jeyakumar Natarajan, José A. Lozano and John E. Moore and has published in prestigious journals such as Bioinformatics, Expert Systems with Applications and BMC Bioinformatics.

In The Last Decade

Daniel Berrar

48 papers receiving 832 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel Berrar Japan 19 333 258 87 75 65 48 866
Borja Calvo Spain 15 637 1.9× 380 1.5× 43 0.5× 20 0.3× 60 0.9× 40 1.4k
Richard Röttger Denmark 13 478 1.4× 143 0.6× 25 0.3× 13 0.2× 32 0.5× 56 909
Guzmán Santafé Spain 8 378 1.1× 273 1.1× 50 0.6× 24 0.3× 49 0.8× 16 914
Carlos Eduardo Ferreira Brazil 17 522 1.6× 104 0.4× 20 0.2× 27 0.4× 28 0.4× 69 1.2k
Geir Kjetil Sandve Norway 23 1.1k 3.4× 138 0.5× 171 2.0× 13 0.2× 18 0.3× 82 2.0k
Lucy Lu Wang United States 19 292 0.9× 523 2.0× 104 1.2× 17 0.2× 82 1.3× 68 1.2k
Zhiguang Chen China 11 361 1.1× 136 0.5× 251 2.9× 15 0.2× 59 0.9× 91 1.1k
Juliane Siebourg‐Polster Switzerland 7 212 0.6× 116 0.4× 26 0.3× 12 0.2× 29 0.4× 16 789
Fernando Gómez Spain 20 343 1.0× 380 1.5× 92 1.1× 4 0.1× 18 0.3× 106 1.8k

Countries citing papers authored by Daniel Berrar

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Daniel Berrar

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Berrar. A scholar is included among the top collaborators of Daniel Berrar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Berrar. Daniel Berrar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Berrar, Daniel. (2025). Encyclopedia of Bioinformatics and Computational Biology. Elsevier eBooks. 3 indexed citations
2.
Berrar, Daniel, Philippe Lopes, & Werner Dubitzky. (2024). A data- and knowledge-driven framework for developing machine learning models to predict soccer match outcomes. Machine Learning. 113(10). 8165–8204. 2 indexed citations
3.
Quinn, Gerry A., İbrahim M. Banat, Daniel Berrar, et al.. (2022). Complementary protein extraction methods increase the identification of the Park Grass Experiment metaproteome. Applied Soil Ecology. 173. 104388–104388. 3 indexed citations
4.
Bonsignore, Riccardo, Daniel Berrar, Martin Swain, et al.. (2021). Identifying and validating the presence of Guanine-Quadruplexes (G4) within the blood fluke parasite Schistosoma mansoni. PLoS neglected tropical diseases. 15(2). e0008770–e0008770. 5 indexed citations
5.
Berrar, Daniel, et al.. (2021). A self-organizing incremental neural network for continual supervised learning. Expert Systems with Applications. 185. 115662–115662. 19 indexed citations
6.
Geyer, Kathrin K., Martin Vickers, Michael Squance, et al.. (2018). The anti-fecundity effect of 5-azacytidine (5-AzaC) on Schistosoma mansoni is linked to dis-regulated transcription, translation and stem cell activities. International Journal for Parasitology Drugs and Drug Resistance. 8(2). 213–222. 15 indexed citations
7.
Berrar, Daniel & Werner Dubitzky. (2018). Should significance testing be abandoned in machine learning?. International Journal of Data Science and Analytics. 7(4). 247–257. 4 indexed citations
8.
Dubitzky, Werner, et al.. (2017). Open International Soccer Database. OSF Preprints (OSF Preprints). 2 indexed citations
9.
Oentaryo, Richard J., Ee‐Peng Lim, David Lo, et al.. (2014). Detecting click fraud in online advertising: a data mining approach. Journal of Machine Learning Research. 15(1). 99–140. 45 indexed citations
10.
Berrar, Daniel, Akihiko Konagaya, & Alfons Schuster. (2013). Turing Test Considered Mostly Harmless. New Generation Computing. 31(4). 241–263. 4 indexed citations
11.
Schuster, Alfons & Daniel Berrar. (2011). The Omnipresent Computing Menace to Information Society. Journal of Advanced Computational Intelligence and Intelligent Informatics. 15(7). 786–792. 2 indexed citations
12.
Berrar, Daniel & Peter Flach. (2011). Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them). Briefings in Bioinformatics. 13(1). 83–97. 96 indexed citations
13.
Deligianni, Elena, Daniel Berrar, Nigel G. Ternan, et al.. (2010). Pseudomonas aeruginosa Cystic Fibrosis isolates of similar RAPD genotype exhibit diversity in biofilm forming ability in vitro. BMC Microbiology. 10(1). 38–38. 81 indexed citations
14.
Graham, Joanna E., Victoria McGilligan, Daniel Berrar, et al.. (2009). Attitudes towards Diagnostic Tests and Therapies for Dry Eye Disease. Ophthalmic Research. 43(1). 11–17. 22 indexed citations
15.
McCann, Mark J., et al.. (2008). Enterolactone restricts the proliferation of the LNCaP human prostate cancer cell line in vitro. Molecular Nutrition & Food Research. 52(5). 567–580. 24 indexed citations
16.
Natarajan, Jeyakumar, Daniel Berrar, Werner Dubitzky, et al.. (2006). Text mining of full-text journal articles combined with gene expression analysis reveals a relationship between sphingosine-1-phosphate and invasiveness of a glioblastoma cell line. BMC Bioinformatics. 7(1). 373–373. 54 indexed citations
17.
Berrar, Daniel, Ian Bradbury, & Werner Dubitzky. (2006). Instance-based concept learning from multiclass DNA microarray data. BMC Bioinformatics. 7(1). 73–73. 18 indexed citations
18.
Berrar, Daniel, et al.. (2005). Towards Data Warehousing and Mining of Protein Unfolding Simulation Data. Journal of Clinical Monitoring and Computing. 19(4-5). 307–317. 12 indexed citations
19.
Natarajan, Jeyakumar, Daniel Berrar, Catherine Hack, & Werner Dubitzky. (2005). Knowledge Discovery in Biology and Biotechnology Texts: A Review of Techniques, Evaluation Strategies, and Applications. Critical Reviews in Biotechnology. 25(1-2). 31–52. 21 indexed citations
20.
Granzow, Martin, Daniel Berrar, Werner Dubitzky, et al.. (2001). Tumor classification by gene expression profiling. 21(1). 16–22. 28 indexed citations

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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