Analyst at DNAlytics
I work as an analyst at DNAlytics, a very dynamic Belgian company that covers the whole development of data-driven personalised medicine solutions, from R&D to market access. My background is in Machine Learning and data analysis.
I received a PhD in June 2015. The goal of my thesis is to improve the interpretability of predictive models built on very high dimensional data. It particularly focuses on heterogeneous biomedical data that contain different types of variables. Selecting a few variables that allow us to predict some clinical outcome greatly helps medical doctors to understand the studied biological process better.
jerome DOT paul AT dnalytics.com
DNAlytics – Offices : CEI2 – Rue Louis de Geer 6, 1348 Louvain-la-Neuve, Belgium
- N Bonnet, J Paul, T Helleputte, et al. Novel insights into the assessment of risk of upper gastrointestinal bleeding in decompensated cirrhotic children. Pediatr Transplant. 2019;e13390, (online: DOI:10.1111/petr.13390)
- Bert Dhondt, Elise De Bleser, Tom Claeys, Sarah Buelens, Nicolaas Lumen, Jo Vandesompele, Anneleen Beckers, Valerie Fonteyne, Kim Van der Eecken, Aurélie De Bruycker, Jérôme Paul, Pierre Gramme, Piet Ost, Discovery and validation of a serum microRNA signature to characterize oligo- and polymetastatic prostate cancer: not ready for prime time, World Journal of Urology, 2018, (online, : DOI:10.1007/s00345-018-2609-8)
- Olesen TK, Denys MA, Goessaert AS, Bruneel E, Decalf V, Helleputte T, Paul J, Gramme P, Everaert K, Development of a multivariate prediction model for nocturia, based on urinary tract etiologies, International Journal of Clinical Practice, 2018, (online: DOI:10.1111/ijcp.13306)
- Lucas Wauters, Françoise Smets, Elisabeth De Greef, Patrick Bontems, Ilse Hoffman, Bruno Hauser, Philippe Alliet, Wim Arts, Harald Peeters, Stephanie Van Biervliet, Isabelle Paquot, Els Van de Vijver, Martine De Vos, Peter Bossuyt, Jean-François Rahier, Olivier Dewit, Tom Moreels, Denis Franchimont, Vincianne Muls, Fernand Fontaine, Edouard Louis, Jean-Charles Coche, Filip Baert, Jérôme Paul, Séverine Vermeire, Geneviève Veereman, Long-term Outcomes with Anti-TNF Therapy and Accelerated Step-up in the Prospective Pediatric Belgian Crohn’s Disease Registry (BELCRO), Inflammatory Bowel Diseases, 2017, (ahead of print)
- L Wauters, F Smets, E De Greef, P Bontems, I Hoffman, B Hauser, P Alliet, W Arts, H Peeters, S Van Biervliet, I Paquot, E Van de Vijver, M De Vos, P Bossuyt, J-F ahier, O Dewit, T Moreels, D Franchimont, V Muls, F Fontaine, E Louis, J-C Coche, J Paul, F Baert, S Vermeire, G Veereman, Type of treating physician is associated with long-term disease outcome in the prospective Belgian paediatric Crohn’s disease registry, Journal of Cronhs & Colitis, Volume 10, pp. S167–S168.
- J. Paul, R. D’Ambrosio and P. Dupont, Kernel methods for heterogeneous feature selection, Neurocomputing, Volume 169, December 2, 2015, pp. 187-195.
- Catherine Lombard, Floriane André, Jérôme Paul, Catherine Wanty, Olivier Vosters, Pierre Bernard, Charles Pilette, Pierre Dupont, Etienne Sokal and Françoise Smets, Clinical Parameters vs Cytokine Profiles as Predictive Markers of IgE-Mediated Allergy in Young Children, PLoS ONE, Volume 10 (7), July 27, 2015, e0132753.
- J. Paul and P. Dupont, Inferring statistically significant features from random forests, Neurocomputing, Volume 150, Part B, February 20, 2015, pp. 471-480, ISSN 0925-2312.
- J. Paul and P. Dupont, Statistically interpretable importance indices for Random Forests, 23rd Annual Machine Learning Conference of Belgium and the Netherlands (BENELEARN), p. 7, Brussels, Belgium, June 6, 2014.
- J. Paul and P. Dupont, Kernel methods for mixed feature selection, ESANN2014, 22th European Symposium on Artificial Neural Networks – Computational Intelligence and Machine Learning, pp. 301-306, Bruges, Belgium, April 23-25, 2014.
- J. Paul, M. Verleysen and P. Dupont, Identification of Statistically Significant Features from Random Forest, ECML workshop on Solving Complex Machine Learning Problems with Ensemble Methods, pp. 69-80, Prague, Czech Republic, September 27, 2013.
- J. Paul, M. Verleysen and P. Dupont, The stability of feature selection and class prediction from ensemble tree classifiers, ESANN 2012, 20th European Symposium on Artificial Neural Networks – Computational Intelligence and Machine Learning, pp. 263-268, Bruges (Belgium), April 25-27, 2012.
- C. Lombard, F. André, C. Wanty, J. Paul, P. Dupont, E. Sokal, F. Smets, Differences in the cytokine profiles of cord blood mononuclear cells from allergic and non-allergic infants (Poster), European Society for Paediatric Gastroenterology, Hepatology, and Nutrition (ESPGHAN’12), Stockholm, Sweden, April 27-28, 2012.
- J. Paul, Feature Selection from Heterogeneous Biomedical Data, PhD Thesis, June 29, 2015, advisor: P. Dupont
- jForest is a generic implementation of tree ensemble methods. It is designed to be very modular and enables easy tuning of the tree induction process, classification criterion and feature importance index. It is developed in Java and bundled in the form of a R package. jForest implements our statistically interpretable feature importance index (see publications).
- HRS2C2, an online calculator for the Hemorrhagic Risk Scoring System in Cirrhotic Children.
- REED: Rapid & Easy Evaluation of Datasets