In preparation / to appear

Berrar D. (2021) Significance Testing for the Comparison of Classifiers over Multiple Data Sets: Pitfalls and Alternatives. Under review.

Quinn G.A., Abdelhameed A., Banat I.M., Berrar D., Doerr S., Dudley E., Francis L.W., Gazze S.A., Hallin I., Matthews P., Swain M.T., Whalley R., and van Keulen G. (2021) Parallel protein extraction methods increase the diversity of protein identification in Park Grass Experiment soil. Under review.

2021

Wiwatcharakoses C. and Berrar D. (2021) A self-organizing incremental neural network for continual supervised learning . Expert Systems with Applications.

Berrar D. and Dubitzky W. (2021) Deep learning in bioinformatics and biomedicine. Editorial to special issue in Briefings in Bioinformatics, May 2021.

Craven H.M., Bonsignore R., Lenis V., Santi N., Berrar D., Swain M., Whiteland H.L., Casini A., Hoffmann K.F. (2021) Identifying and validating the presence of Guanine-Quadruplexes (G4) within the blood fluke parasite Schistosoma mansoni. PLoS Neglected Tropical Diseases.

2020

Wiwatcharakoses C. and Berrar D. (2020) . SOINN+, a self-organizing incremental neural network for unsupervised learning from noisy data streams. Expert Systems with Applications Vol. 143, 113069. [link]

2019

Wiwatcharakoses C. and Berrar D. (2019) Self-organizing incremental neural networks for continual learning. Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI2019), Macao, China, 2019, pp. 6476-6477. [pdf]

Berrar D. and Dubitzky, W. (2019) Should significance testing be abandoned in machine learning? Intl. Journal of Data Science and Analytics 7(4):247–257.

Berrar D., Lopes P., Davis J., and Dubitzky W. (2019) Guest editorial: special issue on machine learning for soccer. Machine Learning 108(1):1-7.

Berrar D., Lopes P., and Dubitzky, W. (2019) Incorporating domain knowledge in machine learning for soccer outcome prediction. Machine Learning 108(1):97-126.

Dubitzky, W., Lopes P., Davis J., and Berrar D. (2019) The Open International Soccer Database for machine learning. Machine Learning 108(1):9-28.

2018

Geyer K.K., Munshia S.E., Vickers M., Squance M., Wilkinson T.J., Berrar D., Chaparroe C., Swain M.T., Hoffmann K.F. (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.

Berrar D. (2018) Introduction to the non-parametric bootstrap. Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 766-773. [pdf preprint]

Berrar D. (2018) Cross-validation. Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 542-545. [pdf preprint]

Berrar D. (2018) Performance measures for binary classification. Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 546-560.

Berrar D. (2018) Bayes' theorem and naive Bayes classifier. Encyclopedia of Bioinformatics and Computational Biology, Volume 1, Elsevier, pp. 403-412. [pdf preprint]

since April 2017 (start of lab)

Berrar D. and Dubitzky W. (2017) On the Jeffreys-Lindley paradox and the looming reproducibility crisis in machine learning. Proceedings of the 2017 IEEE International Conference on Data Science and Advanced Analytics (DSAA2017), Tokyo, Japan, pp. 334-340.

Berrar D., Lopes P., and Dubitzky W. (2017) Caveats and pitfalls in crowdsourcing research: the case of soccer referee bias. International Journal of Data Science and Analytics 4(2):143-151. [link]

Berrar D. (2017) Confidence curves: an alternative to null hypothesis significance testing for the comparison of classifiers. Machine Learning Volume 106, Issue 6, pp. 911–949.

older publications are here