Dr Daniel Berrar

Using p-values for the comparison of classifiers: pitfalls and alternatives (2022-05)
Berrar, Daniel
Data Mining and Knowledge Discovery, 36(3) (pp. 1102-1139)

A Self-Organizing Incremental Neural Network for Continual Supervised Learning (2021-12-15)
Wiwatcharakoses, Chayut and Berrar, Daniel
Expert Systems with Applications, 185, Article 115662

Deep learning in bioinformatics and biomedicine (2021-03)
Berrar, Daniel and Dubitzky, Werner
Briefings in Bioinformatics, 22(2) (pp. 1513-1514)

SOINN+, a Self-Organizing Incremental Neural Network for Unsupervised Learning from Noisy Data Streams (2020-04)
Wiwatcharakoses, Chayut and Berrar, Daniel
Expert Systems with Applications, 143, Article 113069

Should significance testing be abandoned in machine learning? (2019-06-01)
Berrar, Daniel and Dubitzky, Werner
International Journal of Data Science and Analytics, 7(4) (pp. 247-257)

Incorporating domain knowledge in machine learning for soccer outcome prediction (2019-01)
Berrar, Daniel; Lopes, Philippe and Dubitzky, Werner
Machine Learning, 108 (pp. 97-126)

Caveats and pitfalls of ROC analysis in clinical microarray research (and how to avoid them) (2012-01)
Berrar, Daniel and Flach, Peter
Briefings in Bioinformatics, 13(1) (pp. 83-97)

Multidimensional scaling with discrimination coefficients for supervised visualization of high-dimensional data (2011-11)
Berrar, Daniel and Ohmayer, Georg
Neural Computing and Applications, 20(8) (pp. 1211-1218)

Special Issue on Omnipresent Intelligent Computing – New Developments and Societal Impact (2011)
Schuster, Alfons and Berrar, Daniel
Journal of Advanced Computational Intelligence and Intelligent Informatics, 15(7) (pp. 785-785)

Artificial Intelligence in Neuroscience and Systems Biology: Lessons Learnt, Open Problems, and the Road Ahead (2010)
Berrar, Daniel; Sato, Naoyuki and Schuster, Alfons
Advances in Artificial Intelligence, 2010, Article 578309

Pseudomonas aeruginosa cystic fibrosis isolates of similar RAPD genotype exhibit diversity in biofilm forming ability in vitro (2010)
Deligianni, Elena; Pattison, Sally; Berrar, Daniel; Ternan, Nigel G.; Haylock, Richard W.; Moore, John E.; Elborn, Stuart J. and Dooley, James S. G.
BMC Microbiology, 10, Article 38 (2010)(1)

Quo Vadis, Artificial Intelligence? (2010)
Berrar, Daniel; Sato, Naoyuki and Schuster, Alfons
Advances in Artificial Intelligence, 2010, Article 629869

Attitudes towards Diagnostic Tests and Therapies for Dry Eye Disease (2009-12)
Graham, Joanna E.; McGilligan, Victoria E.; Berrar, Daniel; Leccisotti, Antonio; Moore, Jonathan E.; Bron, Anthony J. and Moore, Tara C. B.
Ophthalmic Research, 43(1) (pp. 11-17)

Enterolactone restricts the proliferation of the LNCaP human prostate cancer cell line in vitro (2008)
McCann, Mark J.; Gill, Chris I. R.; Linton, Trevor; Berrar, Daniel; McGlynn, Hugh and Rowland, Ian R.
Molecular Nutrition & Food Research, 52(5) (pp. 567-580)

Knowledge discovery in biology and biotechnology texts: a review of techniques, evaluation strategies, and applications (2008)
Natarajan, J.; Berrar, D.; Hack, C. J. and Dubitzky, W.
Critical reviews in biotechnology, 25(1-2) (pp. 31-52)

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 (2006)
Natarajan, Jeyakumar; Berrar, Daniel; Dubitzky, Werner; Hack, Catherine; Zhang, Yonghong; DeSesa, Catherine; Van Brocklyn, James R. and Bremer, Eric G.
BMC Bioinformatics, 7, Article 373 (2006)

Survival Trees for Analyzing Clinical Outcome in Lung Adenocarcinomas Based on Gene Expression Profiles: Identification of Neogenin and Diacylglycerol Kinase α Expression as Critical Factors (2005)
Berrar, Daniel; Sturgeon, Brian; Bradbury, Ian; Downes, C. Stephen and Dubitzky, Werner
Journal of Computational Biology, 12(5) (pp. 534-544)

Towards Data Warehousing and Mining of Protein Unfolding Simulation Data (2005)
Berrar, Daniel; Stahl, Frederic; Silva, Candida; Rodrigues, J. Rui; Brito, Rui M. M. and Dubitzky, Werner
Journal of clinical monitoring and computing, 19(4-5) (pp. 307-317)

An evaluation of quantitative and qualitative methods of predicting the 2002 FIFA World Cup (2004-06)
O'Donoghue, P. G.; Dubitzky, W.; Lopes, P.; Berrar, D.; Lagan, K.; Hassan, D.; Bairner, A. and Darby, P.
Journal of Sports Sciences, 22(6) (pp. 513-514)

Cross-validation (2024)
Berrar, Daniel
In: Ranganathan, Shoba; Mario, Cannataro and Asif, Mohammad eds. Encyclopedia of Bioinformatics and Computational Biology, 2nd edition
Publisher : Elsevier (In Press)

Performance Measures for Binary Classification (2024)
Berrar, Daniel
In: Ranganathan, Shoba; Mario, Cannataro and Asif, Mohammad eds. Encyclopedia of Bioinformatics and Computational Biology, 2nd edition
Publisher : Elsevier (In Press)

Bayes' Theorem and Naive Bayes Classifier (2024)
Berrar, Daniel
In: Ranganathan, Shoba; Cannataro, Mario and Asif, Mohammed eds. Encyclopedia of Bioinformatics and Computational Biology, 2nd edition
Publisher : Elsevier (In Press)

Introduction to the Non-Parametric Bootstrap (2024)
Berrar, Daniel
In: Ranganathan, Shoba; Mario, Cannataro and Asif, Mohammad eds. Encyclopedia of Bioinformatics and Computational Biology, 2nd edition
Publisher : Elsevier (In Press)

Bayes’ Theorem and Naive Bayes Classifier (2019)
Berrar, Daniel
In: Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian and Cannataro, Mario eds. Encyclopedia of Bioinformatics and Computational Biology. Reference Module in Life Sciences (pp. 403-412)
ISBN : 978-0-12-811432-2 | Publisher : Elsevier

Cross-validation (2019)
Berrar, Daniel
In: Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian and Cannataro, Mario eds. Encyclopedia of Bioinformatics and Computational Biology. Reference Module in Life Sciences (pp. 542-545)
ISBN : 978-0-12-811432-2 | Publisher : Elsevier

Performance Measures for Binary Classification (2019)
Berrar, Daniel
In: Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian and Cannataro, Mario eds. Encyclopedia of Bioinformatics and Computational Biology. Reference Module in Life Sciences (pp. 546-560)
ISBN : 978-0-12-811432-2 | Publisher : Elsevier

Introduction to the Non-Parametric Bootstrap (2019)
Berrar, Daniel
In: Ranganathan, Shoba; Gribskov, Michael; Nakai, Kenta; Schönbach, Christian and Cannataro, Mario eds. Encyclopedia of Bioinformatics and Computational Biology. Reference Module in Life Sciences (pp. 766-773)
ISBN : 978-0-12-811432-2 | Publisher : Elsevier

The UK-Japan Engineering Education League (UKJEEL) Workshop: Rationale, Goals, and Lessons Learned (2023)
Cross, Jeffrey; Berrar, Daniel; Watson, Ian and Smith, Roderick
In : JSEE Annual Conference International Session Proceedings (07 Sep 2023, Hiroshima, Japan) (pp. 14-17)

Self-organizing incremental neural networks for continual learning (2019)
Wiwatcharakoses, Chayut and Berrar, Daniel
In : IJCAI '19: Proceedings of the 28th International Joint Conference on Artificial Intelligence (10 - 16 Aug 2019, Macao, China) (pp. 6476-6477)

On the Jeffreys-Lindley paradox and the looming reproducibility crisis in machine learning (2018)
Berrar, Daniel and Dubitzky, Werner
In : Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA2017) (19-21 Oct 2017, Tokyo, Japan) (pp. 334-340)

On the noise resilience of ranking measures (2016)
Berrar, Daniel
In : Neural Information Processing: 23rd International Conference, ICONIP 2016 (16-21 Oct 2016, Kyoto, Japan) (pp. 47-55)

Can machines make us think? In memory of Alan Turing (1912-1954) (2012)
Berrar, Daniel; Konagaya, Akihiko and Schuster, Alfons
In : The 26th Annual Conference of the Japanese Society for Artificial Intelligence, 2012 (June 12, 2012 - June 15, 2012, 山口県山口市 山口県教育会館等)