Our People

Assist. Prof Enrico GLAAB

Assistant professor / Senior research scientist in Machine Learning and Bioinformatics

Contact

enrico.glaab@uni.lu
(+352) 46 66 44 6186

Details

Functions

Assistant professor / Senior research scientist in Machine Learning and Bioinformatics

In detail

Organisation

Luxembourg Centre for Systems Biomedicine
Department

Biomedical Data Science
Postal address

Roudeneck
1, Boulevard du Jazz
L-4370 ESCH
Campus office

BTL, E04 180
Contact details

enrico.glaab@uni.lu

(+352) 46 66 44 6186

Publications on ORBilu

2018

Assistant Professor, Deputy Course Director and Principal Investigator
Biomedical Data Science Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
2017

Senior Research Scientist, Deputy Course Director and Principal Investigator
Biomedical Data Science Group
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
2015

Research Scientist
Biomedical Data Science Group, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
2011
Research Associate
Bioinformatics Core Unit, Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg

PhD in Computer Science / Bioinformatics
University of Nottingham, United Kingdom
Including the following doctoral fellowship periods:
- 2007 – 2009 Marie Curie Research Fellow
- 2009 – 2010 EPSRC Research Fellow
Doctoral thesis: “Analysing functional genomics data using novel ensemble, consensus and data fusion techniques”
2007

MSc. in Computational Molecular Biology (Honours Degree)
Saarland University, Saarbrücken, Germany
2006

BSc. in Computational Molecular Biology
Saarland University, Saarbrücken, Germany

Enrico Glaab is deputy course director for the Master in Molecular and Computational Biomedicine.

Currently taught courses at Bachelor and Master level:

Course: Top-down systems biology (ISB704, 30 teaching units (TUs) lectures, 30 TUs practicals)
Study programme: Master in Integrated Systems Biology
Semester: 2
Teacher(s): Enrico Glaab

Course: Master thesis (ISB901, 55 TUs)
Study programme: Master in Integrated Systems Biology
Semester: 2
Teacher(s): Thomas Sauter, Enrico Glaab

Currently taught courses at PhD level:

Course: Statistical tests and statistical learning for omics data” (1 ECTS = 25 TUs workload)
Study programme: part of the ELIXIR programme for life science training in Europe
Teacher(s): Enrico Glaab

Previously taught courses at Bachelor and Master level:

Course: Bioinformatics I (BASV94)
Study programme: Bachelor en sciences de la vie – biologie
Semester: 4
Teacher(s): Antonio del Sol, Nikos Vlassis, Venkata Satagopam, Gokhan Ertaylan, Enrico Glaab
Year taught: 2013

Course: Genomics & Databases (ISB101)
Study programme: Master in Integrated Systems Biology
Semester: 2
Teacher(s): Reinhard Schneider, Venkata Satagopam, Janos Binder, Maria Secrier, Maria Biryukov, Enrico Glaab
Year taught: 2012

Course: Bioinformatics (G53BIO, University of Nottingham)
Study programme: Bachelor in Computer Science
Semester: 5
Teacher(s): Jaume Bacardit, Natalio Krasnogor, Enrico Glaab
Year taught: 2010

Recent Selected Publications

R.T.J. Loo, L. Pavelka, G. Mangone, F. Khoury, M. Vidailhet, J.-C. Corvol, E. Glaab, Multi-cohort Machine Learning Identifies Predictors of Cognitive Impairment in Parkinson’s Disease, npj Digital Medicine (2025), 8, 482
M. Soudy, S. Le Bars, E. Glaab, Sex-Dependent Molecular Landscape of Alzheimer’s Disease Revealed by Large-Scale Single-Cell Transcriptomics, Alzheimer’s & Dementia (2025), 21, 2
G. Svinin, R.T.J. Loo, M. Soudy, F. Nasta, S. Le Bars, E. Glaab, Computational systems biology methods for cross-disease comparison of omics data, WIREs Computational Molecular Science (2025), in press
R.T.J. Loo, L. Pavelka, G. Mangone, F. Khoury, M. Vidailhet, J.-C. Corvol, R. Krüger, E. Glaab, Interpretable Machine Learning for Cross-Cohort Prediction of Motor Fluctuations in Parkinson’s Disease, Movement Disorders (2025), in press (doi:10.1002/mds.30223)
A. Rauschenberger, P.N. Nazarov, E. Glaab, Estimating sparse regression models in multi-task learning and transfer learning through adaptive penalisation, Bioinformatics (2025), in press (doi:10.1093/bioinformatics/btaf406)
H. Feng, D. Pogorelov, S. Bode, X. He, J. Ramiro-Garcia, F. Hedin, W. Ammerlaan, M. Konstantinou et al., Multiomics approaches disclose very-early molecular and cellular switches during insect-venom allergen-specific immunotherapy: an observational study, Nature Communications (2024), 15, 10266
H. Scheiblich, F. Eikens, L. Wischhof, S. Opitz, K. Jüngling, C. Cserép, S.V. Schmidt, J. Lambertz et al., Microglia rescue neurons from aggregate-induced neuronal dysfunction and death through tunneling nanotubes, Neuron (2024), 112(18):3106
E. Gómez de Lope, R.T.J. Loo, A. Rauschenberger, M. Ali, L. Pavelka, T.M. Marques, C.P.C. Gomes, R. Krüger, E. Glaab, Comprehensive blood metabolomics profiling of Parkinson’s disease reveals coordinated alterations in xanthine metabolism, npj Parkinson’s Disease (2024), 10, 68
C. Brzenczek, Q. Klopfenstein, T. Hähnel, S. Sapienza, J. Klucken, H. Fröhlich, E. Glaab, Integrating digital gait sensor data with metabolomics and clinical data to predict clinically relevant outcomes in Parkinson‘s disease, npj Digital Medicine (2024), 7, 23
R.T.J. Loo, M. Soudy, F. Nasta, M. Macchi, E. Glaab, Bioinformatics approaches to study molecular sex differences in complex diseases, Briefings in Bioinformatics (2024), 25, 6

Full publications list on Orbilu
ORCID profile

Member of winning team at the international coding challenge on longevity research “LongHack” (https://longhack.org), 2021.
Prize for Best Performing Entrant in the data science and machine learning challenge “Metagenomics Diagnosis for Inflammatory Bowel Disease Challenge (MEDIC)”, by the SBV (Systems Biology Verification) IMPROVER initiative, 2020.
Winner of the international Active Motif Epigenetics Competition for the research project “EpiND: Network-based machine learning analysis of chromatin changes in Parkinson’s disease and Progressive Supranuclear Palsy”, 2019.
Bayer Lindau Fellowship 2015 – chosen by the Lindau selection committee for participation in the Lindau Nobel Laureate Meeting 2015, Germany (sponsored by the Bayer Foundation), 2015.
Winner of the international Geoffrey Beene Alzheimer’s Global NeuroDiscovery Challenge on data mining for Alzheimer’s disease, by the Geoffrey Beene Foundation Alzheimer’s Initiative, the 21st Century BrainTrust, and the New York Academy of Sciences, 2013 (see: http://21cbt.org/21cbt-award ).
Poster Prize Award at the Benelux Bioinformatics Conference, Nijmegen, Netherlands, 2012.
Short-term fellowship by the German Academic Exchange Service (DAAD), EMBL, Heidelberg, Germany, 2011.
ECCB 2010 Travel Fellowship Award to attend the European Conference on Computational Biology 2010, Ghent, Belgium, 2010.
EPSRC Research Fellowship (funded by the Engineering and Physical Sciences Research Council), 2009.
Peer Review Poster Award at Nottingham University Poster Prize event, Nottingham, UK, 2009.
Marie Curie Early Stage Training Research Fellowship (as part of the EU “Marie Curie Actions” programme), 2007.
Member of the German National Merit Foundation (Studienstiftung des Deutschen Volkes) during undergraduate and graduate education in Germany, 2004 – 2007 (now member of the Alumni Association).
Member of the Honours Program for Graduate Students in Computer Science and Bioinformatics at Saarland University, Germany, 2006 – 2007.
Scholarship from the Chair of Bioinformatics at Saarland University, Germany (1000 € stipend for the students with the three best results in the Bioinformatics I exam), 2005.
Winner of the national competition “Jugend forscht” (“Youth Researches”) in the category Mathematics/Computer Science (2001, while attending high school).
Winner of the “Konrad Zuse Youth Prize” for Computer Science awarded by the Eduard-Rhein Trust (2001, while attending high school).

Saarbrücker Zeitung: “Alzheimer greift Gehirnzellen bei Männern und Frauen unterschiedlich an“, 19.02.2025
Webinar on blood metabolomics profiling study for Parkinson’s Disease, 26.06.2024.
Interview with TechnologyNetworks.com on “Biomarker discovery for personalized medicine”, 10.10.2023.
Research Luxembourg: “How should Europe deal with the COVID-19 pandemic in the future?“, 24.08.2021.
Luxemburger Wort: “Pharmaforschung: Laptop statt Labor“, 04.02.2021.
Lëtzebuerger Journal: “La statistique est partout”, 21.10.2019.
Revue – De Magazin fir Lëtzebuerg: “Mind the Brain”, 25.09.2019.
Science.lu: “Wege zur frühzeitigen Diagnose von Alzheimer-Erkrankungen mithilfe eines Videospiels“, 21.09.2019.
Le Quotidien: “Maladie d’Alzheimer : une piste prometteuse trouvée à Belval“, 03/2017.
Letzebuerger Journal: “Den Proteinen auf der Spur [pdf]“.
Drug Target Review: “Researchers find a potential target for anti-Alzheimer treatments”, 01/2017.
DDN News: “Understanding USP9”, 03/2017.
Associazione Alzheimer onlus: “Trovati due nuovi obiettivi potenziali per una cura dell’Alzheimer”, 01/2017.
MedIndia.net: “New Gene Could Be A Potential Target For Alzheimer’s Disease”, 01/2017.
NutecSciences.com: “Araştırmacılar Anti-Alzheimer Tedavileri Için Potansiyel Bir Hedef Buluyor”, 01/2017.
NeuroScienceNews.com: “Potential Target For Alzheimer’s Treatment”, 01/2017.
Bionity.com: “Möglicher Angriffspunkt für Wirkstoffe gegen Alzheimer gefunden”, 01/2017.
ScienceDaily.com: “What hundreds of biomolecules tell us about our nerve cells”, 05/2015.
Science.lu: “LCSB-Wissenschaftler gewinnt weltweiten Forschungswettbewerb”, 11/2013.
Luxemburger Wort: “Kopf an Kopf mit Harvard”, 11/2013.
L’Essentiel: “Un chercheur de l’Uni fait mieux qu’Harvard”, 11/2013.
ScienceDaily.com: “Genetic ‘wiring’ of seeds revealed”, 11/2013.