Profil

GLAAB Enrico

University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Biomedical Data Science

ORCID
0000-0003-3977-7469
Main Referenced Co-authors
MAY, Patrick  (18)
BALLING, Rudolf  (16)
ANTONY, Paul  (15)
KRÜGER, Rejko  (13)
BUTTINI, Manuel  (12)
Main Referenced Keywords
machine learning (35); Parkinson's disease (34); prediction (17); bioinformatics (14); statistics (14);
Main Referenced Unit & Research Centers
Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group) (96)
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) (31)
Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) (14)
Luxembourg Centre for Systems Biomedicine (LCSB): Experimental Neurobiology (Balling Group) (9)
ULHPC - University of Luxembourg: High Performance Computing (7)
Main Referenced Disciplines
Life sciences: Multidisciplinary, general & others (83)
Neurology (67)
Biotechnology (62)
Human health sciences: Multidisciplinary, general & others (51)
Biochemistry, biophysics & molecular biology (29)

Publications (total 146)

The most downloaded
4393 downloads
Ballereau, S., Glaab, E., Kolodkin, A., Chaiboonchoe, A., Biryukov, M., Vlassis, N., Ahmed, H., Pellet, J., Baliga, N., Hood, L., Schneider, R., Balling, R., & Auffray, C. (2013). Functional Genomics, Proteomics, Metabolomics and Bioinformatics for Systems Biology. In A. Prokop & B. Csukás (Eds.), Systems Biology: Integrative Biology and Simulation Tools. Springer. doi:10.1007/978-94-007-6803-1_1 https://hdl.handle.net/10993/1247

The most cited

426 citations (Scopus®)

Shah, P., Fritz, J., Glaab, E., Desai, M. S., Greenhalgh, K., Frachet Bour, A., Niegowska, M., Estes, M., Jäger, C., Seguin-Devaux, C., Zenhausern, F., & Wilmes, P. (2016). A microfluidics-based in vitro model of the gastrointestinal human-microbe interface. Nature Communications, 7, 11535. doi:10.1038/ncomms11535 https://hdl.handle.net/10993/27053

ARENA, G., LANDOULSI, Z., GROSSMANN, D., Payne, T., VITALI, A., DELCAMBRE, S., BARON, A., ANTONY, P., BOUSSAAD, I., BOBBILI, D. R., Sreelatha, A. A. K., PAVELKA, L., J Diederich, N., Klein, C., Seibler, P., GLAAB, E., Foltynie, T., Bandmann, O., Sharma, M., ... COURAGE‐PD Consortium. (2024). Polygenic Risk Scores Validated in Patient-Derived Cells Stratify for Mitochondrial Subtypes of Parkinson's Disease. Annals of Neurology. doi:10.1002/ana.26949
Peer Reviewed verified by ORBi

KLEE, M., AHO, V., MAY, P., Heintz-Buschart, A., LANDOULSI, Z., JONSDOTTIR, S., PAULY, C., PAVELKA, L., DELACOUR, L., KAYSEN, A., Krüger, R., WILMES, P., LEIST, A., Acharya, G., Aguayo, G., Alexandre, M., ALI, M., Ammerlann, W., ARENA, G., ... ZELIMKHANOV, G. (2024). Education as Risk Factor of Mild Cognitive Impairment: The Link to the Gut Microbiome. Journal of Prevention of Alzheimer's Disease. doi:10.14283/jpad.2024.19
Peer reviewed

Gómez de Lope, E., Loo, R. T. J., Rauschenberger, A., Ali, M., Pavelka, L., Marques, T. M., Gomes, C. P. C., Krüger, R., & GLAAB, E. (2024). Comprehensive blood metabolomics profiling of Parkinson's disease reveals coordinated alterations in xanthine metabolism. NPJ Parkinson's Disease, in press (in press).
Peer Reviewed verified by ORBi

Ali, M., Garcia, P., Lunkes, L. P., Sciortino, A., Thomas, M., Heurtaux, T., Grzyb, K., Halder, R., Coowar, D., Skupin, A., Buée, L., Blum, D., Buttini, M., & GLAAB, E. (2024). Single cell transcriptome analysis of the THY-Tau22 mouse model of Alzheimer's disease reveals sex-dependent dysregulations. Cell Death Discovery, 10 (119), 10.1038/s41420-024-01885-9. doi:10.1038/s41420-024-01885-9
Peer Reviewed verified by ORBi

Hähnel, T., Raschka, T., Sapienza, S., Klucken, J., GLAAB, E., Corvol, J.-C., Falkenburger, B., & Fröhlich, H. (2024). Progression subtypes in Parkinson's disease identified by a data driven multi cohort analysis. NPJ Parkinson's Disease, in press (in press). doi:10.1038/s41531-024-00712-3
Peer Reviewed verified by ORBi

Pavelka, L., Rauschenberger, A., Hemedan, A., Ostaszewski, M., GLAAB, E., & Krüger, R. (2024). Converging peripheral blood miRNA profiles in Parkinson's disease and progressive supranuclear palsy. Brain Communications, in press (in press). doi:10.1093/braincomms/fcae187
Peer Reviewed verified by ORBi

Kaya, P., Schaffner-Reckinger, E., Manoharan, G. B., Vukic, V., Kiriazis, A., Ledda, M., Burgos, M., Pavic, K., Gaigneaux, A., GLAAB, E., & Abankwa, D. K. (2024). An improved PDE6D inhibitor combines with Sildenafil to inhibit KRAS-mutant cancer cell growth. Journal of Medicinal Chemistry, in press (in press). doi:10.1021/acs.jmedchem.3c02129
Peer Reviewed verified by ORBi

PAVELKA, L., RAWAL, R., GHOSH, S., PAULY, C., PAULY, L., HANFF, A.-M., KOLBER, P. L., JONSDOTTIR, S., MCINTYRE, D., AZAIZ, K., THIRY, E., Vilasboas, L., SOBOLEVA, E., GIRAITIS, M., TSURKALENKO, O., SAPIENZA, S., DIEDERICH, N., KLUCKEN, J., GLAAB, E., ... NCER-PD Consortium. (19 December 2023). Luxembourg Parkinson’s study -comprehensive baseline analysis of Parkinson’s disease and atypical parkinsonism. Frontiers in Neurology, 14. doi:10.3389/fneur.2023.1330321
Peer Reviewed verified by ORBi

Rosety, I., Zagare, A., Saraiva, C., Nickels, S., Antony, P., Almeida, C., GLAAB, E., Halder, R., Velychko, S., Rauen, T., Schöler, H. R., Bolognin, S., Sauter, T., Jarazo, J., Krüger, R., & Schwamborn, J. C. (18 December 2023). Impaired neuron differentiation in GBA-associated Parkinson's disease is linked to cell cycle defects in organoids. NPJ Parkinson's Disease, 9 (1), 166. doi:10.1038/s41531-023-00616-8
Peer Reviewed verified by ORBi

GLAAB, E. (23 November 2023). Linking digital markers to molecular markers in Parkinson‘s disease [Paper presentation]. DIGIPD General Assembly, Paris, France.

ZAGARE, A., Preciat, G., NICKELS, S. L., Luo, X., MONZEL, A. S., Gomez-Giro, G., ROBERTSON, G., Jaeger, C., Sharif, J., Koseki, H., DIEDERICH, N., GLAAB, E., FLEMING, R. M., & SCHWAMBORN, J. C. (20 November 2023). Omics data integration suggests a potential idiopathic Parkinson's disease signature. Communications Biology, 6 (1), 1179. doi:10.1038/s42003-023-05548-w
Peer Reviewed verified by ORBi

Schimunek, J., Seidl, P., Elez, K., Hempel, T., Le, T., Noé, F., Olsson, S., Raich, L., Winter, R., Gokcan, H., Gusev, F., Gutkin, E. M., Isayev, O., Kurnikova, M. G., Narangoda, C. H., Zubatyuk, R., Bosko, I. P., Furs, K. V., Karpenko, A. D., ... Hermans, T. M. (2023). A community effort in SARS-CoV-2 drug discovery. Molecular Informatics. doi:10.1002/minf.202300262
Peer Reviewed verified by ORBi

MULICA, P., Venegas, C., LANDOULSI, Z., BADANJAK, K., DELCAMBRE, S., TZIORTZIOU, M., HEZZAZ, S., Ghelfi, J., SMAJIC, S., SCHWAMBORN, J. C., Krüger, R., ANTONY, P., MAY, P., GLAAB, E., GRÜNEWALD, A.* , & Pereira, S. L.*. (20 September 2023). Comparison of two protocols for the generation of iPSC-derived human astrocytes. Biological Procedures Online, 25 (1), 26. doi:10.1186/s12575-023-00218-x
Peer Reviewed verified by ORBi
* These authors have contributed equally to this work.

KAYA, P., SCHAFFNER-RECKINGER, E., MANOHARAN, G. B., Vukic, V., Kiriazis, A., LEDDA, M., Burgos, M., PAVIC, K., GAIGNEAUX, A., GLAAB, E., & ABANKWA, D. (2023). An improved PDE6D inhibitor combines with Sildenafil to synergistically inhibit KRAS mutant cancer cell growth. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/58308. doi:10.1101/2023.08.23.554263

Rauschenberger, A., & Glaab, E. (2023). Predicting Dichotomised Outcomes from High-Dimensional Data in Biomedicine. Journal of Applied Statistics. doi:10.1080/02664763.2023.2233057
Peer reviewed

Nikos, V., & GLAAB, E. (25 July 2023). Omics network analysis using mathematical programming [Paper presentation]. 2023 International Conference on Intelligent Systems for Molecular Biology, Lyon, France.

Gómez de Lope, E., Viñas Torné, R., Liò, P., & Glaab, E. (25 July 2023). Graph neural networks for investigating complex diseases: A case study on Parkinson's Disease [Poster presentation]. 31st Annual Intelligent Systems For Molecular Biology and the 22nd Annual European Conference on Computational Biology, Lyon, France.

Grütz, K., Seibler, P., GLAAB, E., Weißbach, A., Diaw, S.-A., Carlisle, F., Blake, D., Klein, C., Lohmann, K., & Grünewald, A. (01 June 2023). Investigating the molecular and cellular basis of ε-sarcoglycan-associated myoclonus-dystonia in an iPSC-derived neuronal model [Paper presentation]. Samuel Belzberg 6th International Dystonia Symposium (IDS6), Dublin, Ireland.
Peer reviewed

Arena, G., Landoulsi, Z., Grossmann, D., Vitali, A., Delcambre, S., Baron, A., Antony, P., Boussaad, I., Bobbili, D. R., Sreelatha, A. A. K., Pavelka, L., Klein, C., Seibler, P., Glaab, E., Sharma, M., Krüger, R., May, P., & Grünewald, A. (2023). Polygenic risk scores validated in patient-derived cells stratify for mitochondrial subtypes of Parkinson\textquoterights disease 2023.05.12.23289877. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/55367. doi:10.1101/2023.05.12.23289877

ALI, M.* , GARCIA, P.* , Laetitia P. Lunkes, SCIORTINO, A., THOMAS, M., HEURTAUX, T., GRZYB, K., HALDER, R., SKUPIN, A., MITTELBRONN, M., BUTTINI, M., & GLAAB, E. (12 May 2023). Gene Regulatory Network Analysis of Single-Cell Transcriptomes from THY-Tau22 Mice Reveals Sex-Dependent Immune Dysregulation associated with Alzheimer-like pathology [Poster presentation]. The 7th Venusberg Meeting on Neuroinflammation, Belval, Luxembourg.
* These authors have contributed equally to this work.

GOMEZ DE LOPE, E., & GLAAB, E. (11 May 2023). Pathway-based machine learning analysis of Parkinson’s disease transcriptomics data reveals coordinated alterations in inflammatory pathways [Poster presentation]. 7th Venusberg Meeting on Neuroinflammation, Luxembourg.
Peer reviewed

Roomp, K., GLAAB, E., & Schneider, J. (11 May 2023). Sex-specific Transcriptomic, Proteomic Differences across Multiple Alzheimer's Disease Cohorts [Poster presentation]. 7th Venusberg Meeting on Neuroinflammation, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Pauly, C., GLAAB, E., Hansen, M., Martin-Gallausiaux, C., Ledda, M., Marques, T., Wilmes, P., Krüger, R., & Diederich, N. (26 January 2023). MORE SMOKE THAN FIRE NO SPEEDING UP OF PARKINSON‘S DISEASE AFTER COVID-10 LOCKDOWN [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Jarazo, J., Santos Da Silva, E., GLAAB, E., Perez, D., & Schwamborn, J. (26 January 2023). SARS-COV-2 INDUCES DOPAMINERGIC NEURON LOSS IN MIDBRAIN ORGANOIDS [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Rauschenberger, A., Landoulsi, Z., van de Wiel, M. A., & Glaab, E. (2023). Penalised regression with multiple sources of prior effects. Bioinformatics, in press. doi:10.48550/arXiv.2212.08581
Peer Reviewed verified by ORBi

Sieberts, S. K., Borzymowski, H., Guan, Y., Huang, Y., Matzner, A., Page, A., Bar-Gad, I., Beaulieu-Jones, B., El-Hanani, Y., Goschenhofer, J., Javidnia, M., Keller, M. S., Li, Y.-C., Saqib, M., Smith, G., Stanescu, A., Venuto, C. S., Zielinski, R., Glaab, E., ... BEAT-PD, D. C. C. (Other coll.). (2023). Developing better digital health measures of Parkinson's disease using free living data and a crowdsourced data analysis challenge. PLoS Digital Health, 2 (3), 0000208. doi:10.1371/journal.pdig.0000208
Peer reviewed

Tranchevent, L.-C., Halder, R., & Glaab, E. (2023). Systems level analysis of sex-dependent gene expression changes in Parkinson’s disease. NPJ Parkinson's Disease, 9 (8). doi:10.1038/s41531-023-00446-8
Peer Reviewed verified by ORBi

Khachatryan, L., Xiang, Y., Ivanov, A., Glaab, E., Graham, G., Granata, I., Giordano, M., Maddalena, L., Piccirillo, M., Manipur, I., Baruzzo, G., Cappellato, M., Avot, B., Stan, A., Battey, J., Lo Sasso, G., Boue, S., Ivanov, N. V., Peitsch, M. C., ... Poussin, C. (2023). Results and Lessons Learned from the sbv IMPROVER Metagenomics Diagnostics for Inflammatory Bowel Disease Challenge. Scientific Reports, in press. doi:10.1038/s41598-023-33050-0
Peer reviewed

Vlassis, N., & Glaab, E. (2023). Network perturbation analysis of omics data for complex diseases using convex optimization [Poster presentation]. 31st Annual Intelligent Systems For Molecular Biology and the 22nd Annual European Conference on Computational Biology (ISMB/ECCB 2023), Lyon, France.

Bergquist, T., Schaffter, T., Yan, Y., Yu, T., Prosser, J., Gao, J., Chen, G., Charzewski, Ł., Nawalany, Z., Brugere, I., Retkute, R., Prusokas, A., Prusokas, A., Choi, Y., Lee, S., Choe, J., Lee, I., Kim, S., Kang, J., ... Charzewski, Ł. (2023). Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine. Journal of the American Medical Informatics Association. doi:10.1093/jamia/ocad159
Peer reviewed

GOMEZ DE LOPE, E., & GLAAB, E. (2023). Unravelling Inflammatory Pathways in Parkinson's Disease: Insights from Pathway-Based Machine Learning Analysis of Transcriptomics Data [Paper presentation]. RIKEN-Tsinghua International Summer Program (RISP), Tokyo, Japan.

Landoulsi, Z., Arena, G., Grossmann, D., Vitali, A., Delcambre, S., Antony, P., Boussaad, I., Reddy Bobbili, D., Pavelka, L., GLAAB, E., Sharma, M., Krüger, R., May, P., & Grünewald, A. (2023). Functional validation of a mitochondria-specific polygenic risk score in patient-based models for stratification of idiopathic Parkinson's disease [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Zagare, A., Kurlovics, J., Stalidzans, E., Gomez Giro, G., Antony, P., Jäger, C., GLAAB, E., & Schwamborn, J. (January 2023). ANALYSIS OF INSULIN RESISTANCE AS A RISK FACTOR FOR PARKINSON’S DISEASE [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Ohnmacht, J., Bobbili, D., Meyrath, M., Remmers, D., GLAAB, E., Wyman, S., Kaye, J., May, P., Finkbeiner, S., & Krüger, R. (2023). IDENTIFICATION AND FUNCTIONAL CHARACTERIZATION OF VPS41 AS A POTENTIAL GENETIC MODIFIER OF PENETRANCE IN P.G2019S LRRK2-ASSOCIATED PARKINSON’S DISEASE [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Rawal, R., Shoaib, M., Pavelka, L., Ghosh, S., Landoulsi, Z., Pachchek, S., Rauschenberger, A., Jubal, E., Vaillant, M., Aguayo, G., Roomp, K., Gomes, C., Marques, T., Claire, P., Laure, P., McIntyre, D., Terwindt, O., Sandt, E., Hanff, A., ... Krüger, R. (2023). DATA-DRIVEN SUBTYPES OF PARKINSON’S DISEASE USING MACHINE LEARNING IN LUXEMBOURG PARKINSON STUDY [Poster presentation]. Precision Medicine in Parkinson’s Disease, Esch-sur-Alzette, Luxembourg.
Peer reviewed

Pavelka, L., Rauschenberger, A., GLAAB, E., & Krüger, R. (2023). Converging peripheral blood micro-RNA profiles in idiopathic Parkinson’s disease and progressive supranuclear palsy [Poster presentation]. 18th International meeting of the GEoPD consortium, Antwerp, Belgium.
Peer reviewed

Loo Ting Jiin, R., & GLAAB, E. (2023). Cross-cohort prognosis of levodopa-induced dyskinesia in Parkinson’s disease [Poster presentation]. Basel Computational Biology Conference, Basel, Switzerland.
Peer reviewed

Gómez de Lope, E., & Glaab, E. (18 September 2022). Machine learning applied to higher order functional representations of omics data reveals biological pathways associated with Parkinson‘s Disease [Poster presentation]. European Conference on Computational Biology - European Student Council Symposium, Sitges, Barcelona, Spain.
Peer reviewed

Pavelka, L., Rauschenberger, A., Landoulsi, Z., Pachchek, S., Marques, T., Gomes, C., Glaab, E., May, P., Krüger, R., & NCER-PD, C. (2022). Body-First Subtype of Parkinson's Disease with Probable REM-Sleep Behavior Disorder Is Associated with Non-Motor Dominant Phenotype. Journal of Parkinson's Disease. doi:10.3233/JPD-223511
Peer Reviewed verified by ORBi

Pavelka, L., Rauschenberger, A., Landoulsi, Z., Pachchek, S., May, P., Glaab, E., NCER-PD, C., & Krüger, R. (Other coll.). (2022). Age at onset as stratifier in idiopathic Parkinson's disease - effect of ageing and polygenic risk score on clinical phenotypes. NPJ Parkinson's Disease, 9 (8), 102. doi:10.1038/s41531-022-00342-7
Peer Reviewed verified by ORBi

Balta, M. G., Schreurs, O., Halder, R., Küntziger, T. M., Saetre, F., Blix, I. J. S., Baekkevold, E. S., Glaab, E., & Schenck, K. (2022). RvD1(n-3 DPA) Downregulates the Transcription of Pro-Inflammatory Genes in Oral Epithelial Cells and Reverses Nuclear Translocation of Transcription Factor p65 after TNF-α Stimulation. International Journal of Molecular Sciences, 23 (23). doi:10.3390/ijms232314878
Peer Reviewed verified by ORBi

Balta, M. G., Schreurs, O., Hansen, T. V., Tungen, J. E., Vik, A., Glaab, E., Küntziger, T. M., Schenck, K., Baekkevold, E. S., & Blix, I. J. S. (2022). Expression and function of resolvin RvD1(n-3 DPA) receptors in oral epithelial cells. European Journal of Oral Sciences, 130 (4), 12883. doi:10.1111/eos.12883
Peer Reviewed verified by ORBi

Garcia, P., Wemheuer, W., Uriarte, O., Michelucci, A., Masuch, A., Brioschi, S., Weihofen, A., Koncina, E., Coowar, D., Heurtaux, T., Glaab, E., Balling, R., Sousa, C., Kaoma, T., Nicot, N., Pfander, T., Schulz-Schaeffer, W., Allouche, A., Fischer, N., ... Buttini, M. (2022). Neurodegeneration and neuroinflammation are linked, but independent of a-synuclein inclusions, in a seeding/spreading mouse model of Parkinson's disease. Glia. doi:10.1002/glia.24149
Peer Reviewed verified by ORBi

Fröhlich, H., Bontridder, N., Petrovska-Delacréta, D., Glaab, E., Kluge, F., Yacoubi, M. E., Marín Valero, M., Corvol, J.-C., Eskofier, B., Van Gyseghem, J.-M., Lehericy, S., Winkler, J., & Klucken, J. (2022). Leveraging the Potential of Digital Technology for Better Individualized Treatment of Parkinson's Disease. Frontiers in Neurology, 13, 788427. doi:10.3389/fneur.2022.788427
Peer Reviewed verified by ORBi

Trezzi, J.-P., Aho, V., Jäger, C., Schade, S., Janzen, A., Hickl, O., Kunath, B., Thomas, M., Schmit, K., Garcia, P., Sciortino, A., Martin-Gallausiaux, C., Halder, R., Huarte, O. U., Heurtaux, T., Heins-Marroquin, U., Gomez-Giro, G., Weidenbach, K., Delacour, L., ... Wilmes, P. (2022). An archaeal compound as a driver of Parkinson’s disease pathogenesis. (1). ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/51987. doi:10.21203/rs.3.rs-1827631/v1

Diaz-Uriarte, R., Gómez de Lope, E., Giugno, R., Fröhlich, H., Nazarov, P., Nepomuceno-Chamorro, I. A., Rauschenberger, A., & Glaab, E. (2022). Ten Quick Tips for Biomarker Discovery and Validation Analyses Using Machine Learning. PLoS Computational Biology, 18 (8), 1010357. doi:10.1371/journal.pcbi.1010357
Peer Reviewed verified by ORBi

Ali, M., Huarte, O., Heurtaux, T., Garcia, P., Rodriguez, B. P., Grzyb, K., Halder, R., Skupin, A., Buttini, M., & Glaab, E. (2022). Single-cell transcriptional profiling and gene regulatory network modeling in Tg2576 mice reveal gender-dependent molecular features preceding Alzheimer-like pathologies. Molecular Neurobiology, in press (doi:10.1007/s12035-022-02985-2) (in press). doi:10.1007/s12035-022-02985-2
Peer Reviewed verified by ORBi

Pauly, C., Glaab, E., Hansen, M., Martin-Gallausiaux, C., Ledda, M., Marques, T., Wilmes, P., Krüger, R., & Consortium, N.-P. (2022). Parkinson's Disease progression, resilience and inflammation markers during the COVID-19 pandemic. Movement Disorders, in press (doi: 10.1002/mds.29212) (in press). doi:10.1002/mds.29212
Peer Reviewed verified by ORBi

Glaab, E., Manoharan, G. B., & Abankwa, D. (23 August 2021). A Pharmacophore Model for SARS-CoV-2 3CLpro Small Molecule Inhibitors and in Vitro Experimental Validation of Computationally Screened Inhibitors. Journal of Chemical Information and Modeling, 61 (8), 4082-4096. doi:10.1021/acs.jcim.1c00258
Peer Reviewed verified by ORBi

Glaab, E. (13 January 2021). Artificial intelligence in personalized medicine [Paper presentation]. Symposium on Artificial Intelligence in Personaized Medicine, Amsterdam, Netherlands.

Rauschenberger, A., Glaab, E., & van de Wiel, M. (2021). Predictive and interpretable models via the stacked elastic net. Bioinformatics, 37 (14), 2012–2016. doi:10.1093/bioinformatics/btaa535
Peer reviewed

Giovagnoni, C., Ali, M., Eijssen, L. M. T., Maes, R., Choe, K., Mulder, M., Kleinjans, J., del Sol, A., Glaab, E., Mastroeni, D., Delvaux, E., Coleman, P., Losen, M., Pishva, E., Martinez, P. M., & van den Hove, D. L. A. (2021). Altered sphingolipid function in Alzheimer's disease; a gene regulatory network approach. Neurobiology of Aging, in press (in press). doi:10.1016/j.neurobiolaging.2021.02.001
Peer Reviewed verified by ORBi

Imm, J., Pishva, E., Ali, M., Kerrigan, T. L., Jeffries, A., Burrage, J., Glaab, E., Allen, N., & Lunnon, K. (2021). Characterization of DNA Methylomic signatures in induced pluripotent stem cells during neuronal differentiation. Frontiers in Cell and Developmental Biology. doi:10.3389/fcell.2021.647981
Peer Reviewed verified by ORBi

Sieberts, S., Schaff, J., Duda, M., Pataki, B., Sun, M., Snyder, P., Daneault, J., Parisi, F., Costante, G., Rubin, U., Banda, P., Chae, Y., Neto, E., Dorsey, E., Aydin, Z., Chen, A., Elo, L., Espino, C., Glaab, E., ... Omberg, L. (2021). Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge. npj Digital Medicine, 4 (53). doi:10.1038/s41746-021-00414-7
Peer Reviewed verified by ORBi

Rauschenberger, A., & Glaab, E. (2021). Predicting correlated outcomes from molecular data. Bioinformatics, 37 (21), 3889–3895. doi:10.1093/bioinformatics/btab576
Peer reviewed

Ostaszewski, M., Niarakis, A., Mazein, A., Kuperstein, I., Phair, R., Orta-Resendiz, A., Singh, V., Aghamiri, S. S., Acencio, M. L., Glaab, E., Ruepp, A., Fobo, G., Montrone, C., Brauner, B., Frishman, G., Monraz Gómez, L. C., Somers, J., Hoch, M., Kumar Gupta, S., ... Schneider, R. (2021). COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms. Molecular Systems Biology, 17 (10), 10387. doi:10.15252/msb.202110387
Peer Reviewed verified by ORBi

Badanjak, K., Mulica, P., Smajic, S., Delcambre, S., Tranchevent, L.-C., Diederich, N., Rauen, T., Schwamborn, J. C., Glaab, E., Cowley, S. A., Antony, P., Pereira, S. L., Venegas, C., & Grünewald, A. (2021). iPSC-Derived Microglia as a Model to Study Inflammation in Idiopathic Parkinson's Disease. Frontiers in Cell and Developmental Biology, 9, 740758. doi:10.3389/fcell.2021.740758
Peer Reviewed verified by ORBi

Glaab, E., Rauschenberger, A., Banzi, R., Gerardi, C., Garcia, P., Demotes, J., & PERMIT group. (2021). Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review. BMJ Open, 11 (12), 053674. doi:10.1136/bmjopen-2021-053674
Peer reviewed

Ganzinger, M., Glaab, E., Kerssemakers, J., Nahnsen, S., Sax, U., Schaadt, N. S., Schapranow, M.-P., & Tiede, T. (2021). Biomedical and Clinical Research Data Management. In O. Wolkenhauer, Systems Medicine - Integrative, Qualitative and Computational Approaches (pp. 532-543). Elsevier. doi:10.1016/B978-0-12-801238-3.11621-6
Peer reviewed

Czypionka, T., Iftekhar, E., Prainsack, B., Priesemann, V., Bauer, S., Valdez, A. C., Cuschieri, S., Glaab, E., Grill, E., Krutzinna, J., Lionis, C., Machado, H., Martins, C., Pavlakis, G., Perc, M., Petelos, E., Pickersgill, M., Skupin, A., Schernhammer, E., ... Wilmes, P. (2021). The benefits, costs and feasibility of a low incidence COVID-19 strategy. The Lancet Regional Health - Europe, 12 (100193). doi:10.1016/j.lanepe.2021.100294
Peer reviewed

Priesemann, V., Balling, R., Bauer, S., Beutels, P., Valdez, A. C., Cuschieri, S., Czypionka, T., Dumpis, U., Glaab, E., Grill, E., Hotulainen, P., Iftekhar, E. N., Krutzinna, J., Lionis, C., Machado, H., Martins, C., McKee, M., Pavlakis, G. N., Perc, M., ... Willeit, P. (2021). The benefits of low COVID-19 incidence in Europe. The Lancet, 398 (10303), 838-839. doi:10.1016/S0140-6736(21)01808-0
Peer reviewed

Iftekhar, E. N., Priesemann, V., Balling, R., Bauer, S., Beutels, P., Valdez, A. C., Cuschieri, S., Czypionka, T., Dumpis, U., Glaab, E., Grill, E., Hanson, C., Hotulainen, P., Klimek, P., Kretzschmar, M., Krüger, T., Krutzinna, J., Low, N., Machado, H., ... Willeit, P. (2021). A look into the future of the COVID-19 pandemic in Europe: an expert consultation. The Lancet Regional Health. Europe, 8 (100185). doi:10.1016/j.lanepe.2021.100185
Peer reviewed

Glaab, E. (02 December 2020). Scoping review on machine learning methods for stratification [Paper presentation]. Personalized Medicine Trials (PERMIT) Workshop.

Acharya, S., Salgado-Somoza, A., Stefanizzi, F. M., Lumley, A. I., Zhang, L., Glaab, E., May, P., & Devaux, Y. (06 September 2020). Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson’s Disease. International Journal of Molecular Sciences, 21 (18), 6513. doi:10.3390/ijms21186513
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Hartl, D.* , May, P.* , Gu, W.* , Mayhaus, M., Pichler, S., Spaniol, C., Glaab, E., Bobbili, D. R., Antony, P., Köglsberger, S., Kurz, A., Grimmer, T., Morgan, K., Vardarajan, B. N., Reitz, C., Hardy, J., Bras, J., Guerreiro, R., AESG, ... Riemenschneider, M. (09 July 2020). A rare loss-of function variant of ADAM17 is associated with late-onset familial Alzheimer disease. Molecular Psychiatry, 25 (3), 629-639. doi:10.1038/s41380-018-0091-8
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* These authors have contributed equally to this work.

Hendrickx, D. M., & Glaab, E. (2020). Comparative transcriptome analysis of Parkinson’s disease and Hutchinson-Gilford progeria syndrome reveals shared susceptible cellular network processes. BMC Medical Genomics, 13 (114). doi:10.1186/s12920-020-00761-6
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DeBenedictis, M., Gindzin, Y., Glaab, E., & Anand-Apte, B. (2020). A novel TIMP3 mutation associated with a retinitis pigmentosa-like phenotype. Ophthalmic Genetics, 41 (5), 480-484. doi:10.1080/13816810.2020.1795889
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Greuel, A., Trezzi, J.-P., Glaab, E., Ruppert, M. C., Maier, F., Jäger, C., Hodak, Z., Lohmann, K., Yilong, M., Eidelberg, D., Timmermann, L., Hiller, K., Tittgemeyer, M., Drzezga, A., Diederich, N., & Eggers, C. (2020). GBA variants in Parkinson’s disease: clinical, metabolomic and multimodal neuroimaging phenotypes. Movement Disorders, 35 (12), 2201-2210. doi:10.1002/mds.28225
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Hendrickx, D. M., Garcia, P., Ashrafi, A., Sciortino, A., Schmit, K., Kollmus, H., Nicot, N., Kaoma, T., Vallar, L., Buttini, M., & Glaab, E. (2020). A new synuclein-transgenic mouse model for early Parkinson's reveals molecular features of preclinical disease. Molecular Neurobiology, 58, 576-602. doi:10.1007/s12035-020-02085-z
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Tanevski, J., Nguyen, T., Truong, B., Karaiskos, N., Eren, M., Zhang, X., Shu, C., Hu, Y., Pham, H. V. V., Li, X., Le, T., Tarca, A., Bhatti, G., Romero, R., Karathanasis, N., Loher, P., Chen, Y., Ouyang, Z., Mao, D., ... Saez-Rodriguez, J. (2020). Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics. Life Science Alliance, 3 (11), 202000867. doi:10.26508/LSA.202000867
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Boussaad, I., Obermaier, C. D., Hanss, Z., Bobbili, D. R., Bolognin, S., Glaab, E., Wołyńska, K., Weisschuh, N., De Conti, L., May, C., Giesert, F., Grossmann, D., Lambert, A., Kirchen, S., Biryukov, M., Burbulla, L. F., Massart, F., Bohler, J., Cruciani, G., ... Krüger, R. (2020). A patient-based model of RNA mis-splicing uncovers treatment targets in Parkinson's disease. Science Translational Medicine, 12 (560). doi:10.1126/scitranslmed.aau3960
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Berenguer, C., Grossmann, D., Massart, F., Antony, P., Burbulla, L., Glaab, E., Imhoff, S., Trinh, J., Seibler, P., Grünewald, A., & Krüger, R. (2019). Variants in Miro1 cause alterations of ER-mitochondria contact sites in fibroblasts from Parkinson's disease patients. Journal of Clinical Medicine. doi:10.3390/jcm8122226
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Glaab, E. (01 November 2019). Computational analysis of molecular network perturbations in complex diseases [Paper presentation]. Digital possibilities in research, Oslo, Norway.

Grossmann, D., Berenguer, C., Bellet, M. E., Scheibner, D., Bohler, J., Massart, F., Rapaport, D., Skupin, A., Fouquier d'Hérouël, A., Sharma, M., Ghelfi, J., Rakovic, A., Lichtner, P., Antony, P., Glaab, E., May, P., Dimmer, K. S., Fitzgerald, J. C., Grünewald, A., & Krüger, R. (2019). Mutations in RHOT1 disrupt ER-mitochondria contact sites interfering with calcium homeostasis and mitochondrial dynamics in Parkinson's disease. Antioxidants & redox signaling. doi:10.1089/ars.2018.7718
Peer reviewed

Glaab, E., Trezzi, J.-P., Greuel, A., Jäger, C., Hodak, Z., Drzezga, A., Timmermann, L., Tittgemeyer, M., Diederich, N. J., & Eggers, C. (2019). Integrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease. Neurobiology of Disease, 124 (1), 555-562. doi:10.1016/j.nbd.2019.01.003
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Glaab, E. (January 2019). Machine learning analysis of metabolomics and neuro-imaging data for Parkinson’s disease [Paper presentation]. PD-Strat meeting, Tuebingen, Germany.

Glaab, E., Antony, P., Köglsberger, S., Forster, J. I., Cordero-Maldonado, M. L., Crawford, A., Garcia, P., & Buttini, M. (2019). Transcriptome profiling data reveals Ubiquitin-Specific Peptidase 9 knockdown effects. Data in Brief, 25 (1), 104130. doi:10.1016/j.dib.2019.104130
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Glaab, E. (2019). Algorithmic improvement of public cellular pathway and process definitions [Paper presentation]. PD-Strat meeting, Belval, Luxembourg.

Hertel, J., Harms, A. C., Heinken, A., Baldini, F., Thinnes, C. C., Glaab, E., Vasco, D., Pietzner, M., Stewart, I. D., Wareham, N. J., Langenberg, C., Trenkwalder, C., Krüger, R., Hankemeier, T., Fleming, R. M. T., Mollenhauer, B., & Thiele, I. (2019). Integrated Analyses of Microbiome and Longitudinal Metabolome Data Reveal Microbial-Host Interactions on Sulfur Metabolism in Parkinson’s Disease. Cell Reports, 29 (7), 1767-1777. doi:10.1016/j.celrep.2019.10.035
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Nickels, S., Walter, J., Bolognin, S., GERARD, D., Jäger, C., Qing, X., Tisserand, J., Jarazo, J., Hemmer, K., Harms, A., Halder, R., Lucarelli, P., Berger, E., Antony, P., Glaab, E., Hankemeier, T., Klein, C., Sauter, T., Sinkkonen, L., & Schwamborn, J. C. (2019). Impaired serine metabolism complements LRRK2-G2019S pathogenicity in PD patients. Parkinsonism and Related Disorders. doi:10.1016/j.parkreldis.2019.09.018
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Zhang, Z., Jung, P., Groues, V., May, P., Linster, C., & Glaab, E. (2019). BSA4Yeast: Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data. GigaScience, 8 (6), 060. doi:10.1093/gigascience/giz060
Peer Reviewed verified by ORBi

Bolognin, S., Fossépré, M., Qing, X., Jarazo, J., Ščančar, J., Lucumi Moreno, E., Nickels, S., Wasner, K., Ouzren, N., Walter, J., Grünewald, A., Glaab, E., Salamanca, L., Fleming, R. M. T., Antony, P., & Schwamborn, J. C. (2018). 3D Cultures of Parkinson's Disease‐Specific Dopaminergic Neurons for High Content Phenotyping and Drug Testing. Advanced Science. doi:10.1002/advs.201800927
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Glaab, E., Trezzi, J.-P., Greuel, Jäger, C., Hodak, Z., Timmermann, L., Tittgemeyer, M., Diederich, N. J., & Eggers, C. (08 October 2018). Combining PET imaging and blood metabolomics data to improve machine learning models for Parkinson’s disease diagnosis [Poster presentation]. 2018 International Congress of the International Parkinson and Movement Disorders Society, Esch-sur-Alzette, Luxembourg.

Glaab, E. (16 July 2018). Integrative analysis of mitochondrial changes in Parkinson’s disease [Paper presentation]. MitoPD Meeting, Tuebingen, Germany.

Glaab, E. (July 2018). Computational systems biology approaches for Parkinson's disease. Cell and Tissue Research, 373 (1), 91–109. doi:10.1007/s00441-017-2734-5
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Glaab, E. (28 June 2018). Combined analysis of neuroimaging and metabolomics data for Parkinson’s disease [Paper presentation]. MetimagPD, Cologne, Germany. doi:10.1016/j.nbd.2019.01.003

Nyffeler, J., Chovancova, P., Dolde, X., Holzer, A.-K., Purvanov, V., Kindinger, I., Kerins, A., Higton, D., Silvester, S., van Vugt-Lussenburg, B. M. A., Glaab, E., van der Burg, B., Maclennan, R., Legler, D. F., & Leist, M. (March 2018). A structure-activity relationship linking non-planar PCBs to functional deficits of neural crest cells: new roles for connexins. Archives of Toxicology, 92 (3), 1225–1247. doi:10.1007/s00204-017-2125-4
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Trezzi, J.-P., Greuel, A., Glaab, E., Hodak, Z., Timmermann, L., Jäger, C., Diederich, N., & Eggers, C. (2018). Combining Metabolomics and Neuroimaging in mid-stage Parkinson’s Disease. A Proof of Concept for Cross-Fertilization. Neurology, 90 (15), 3066.
Peer Reviewed verified by ORBi

Greuel, A., Trezzi, J.-P., Glaab, E., Jäger, C., Hodak, Z., Lohmann, K., Klein, C., Timmermann, L., Drzezga, A., Tittgemeyer, M., Diederich, N., & Eggers, C. (2018). FDG-PET and metabolomics in PD-associated GBA variants. Movement Disorders, 33 (2), 599.
Peer Reviewed verified by ORBi

Köglsberger, S., Cordero Maldonado, M. L., Antony, P., Forster, J., Garcia, P., Buttini, M., Crawford, A. D., & Glaab, E. (December 2017). Gender-specific expression of ubiquitin-specific peptidase 9 modulates tau expression and phosphorylation: possible implications for tauopathies. Molecular Neurobiology, 54 (10), 7979–7993. doi:10.1007/s12035-016-0299-z
Peer Reviewed verified by ORBi

Ashrafi, A., Garcia, P., Kollmus, H., Schughart, K., del Sol Mesa, A., Buttini, M., & Glaab, E. (October 2017). Absence of regulator of G-protein signaling 4 does not protect against dopamine neuron dysfunction and injury in the mouse 6-hydroxydopamine lesion model of Parkinson's disease. Neurobiology of Aging, 58, 30-33. doi:10.1016/j.neurobiolaging.2017.06.008
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Fitzgerald, J. C., Zimprich, A., Carvajal-Berrio, D. A., Schindler, K. M., Maurer, B., Schulte, C., Bus, C., Hauser, A.-K., Kübler, M., Lewin, R., Bobbili, D. R., Schwarz, L. M., Vartholomaiou, E., Brockmann, K., Wüst, R., Madlung, J., Nordheim, A., Riess, O., Martins, L. M., ... Krüger, R. (24 August 2017). Metformin reverses TRAP1 mutation-associated alterations in mitochondrial function in Parkinson's disease. Brain: a Journal of Neurology, 140 (9), 2444-2459. doi:10.1093/brain/awx202
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Blauwendraat, C., Faghri, F., Pihlstrom, L., Geiger, J. T., Elbaz, A., Lesage, S., May, P., Aude, N., Abramzon, Y., Murphy, N. A., Gibbs, J. R., Ryten, M., Ferrari, R., Bras, J., Guerreiro, R., Williams, J., Sims, R., Lubbe, S., Hernandez, D. G., ... Scholz, S. W. (2017). NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases. Neurobiology of Aging. doi:10.1016/j.neurobiolaging.2017.05.009
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Singh, C., Glaab, E., & Linster, C. (2017). Molecular Identification of D-Ribulokinase in Budding Yeast and Mammals. Journal of Biological Chemistry, 292 (3), 1005-1028. doi:10.1074/jbc.M116.760744
Peer Reviewed verified by ORBi

Glaab, E. (2017). Integrative analysis of mitochondrial molecular changes in Parkinson’s disease [Paper presentation]. MitoPD Meeting, Germany.

Glaab, E. (2017). Quantitative feature extraction for machine learning analysis of resting-state fMRI data [Paper presentation]. MetimagPD Meeting, Esch-sur-Alzette, Luxembourg.

Glaab, E. (2017). Biomedical Data Science at LCSB [Paper presentation]. Biomedicine Vision Meeting 2017, Luxembourg, Luxembourg.

Hartl, D., May, P., Gu, W., Mayhaus, M., Glaab, E., Antony, P., Bobbili, D. R., Köglsberger, S., Pichler, S., Spaniol, C., Kurz, A., Balling, R., Schneider, J., & Riemenschneider, M. (2017). IDENTIFICATION OF A RARE GENE VARIANT THAT IS ASSOCIATED WITH FAMILIAL ALZHEIMER DISEASE AND REGULATES APP EXPRESSION. Alzheimer's and Dementia: the Journal of the Alzheimer's Association, 13 (7, Supplement), 648. doi:10.1016/j.jalz.2017.06.758
Peer reviewed

Glaab, E. (07 October 2016). Analysis of protein druggability in the alpha-synuclein regulatory network [Paper presentation]. 3rd International Parkinson's Disease Symposium.

Greenhalgh, K., Fritz, J., Letellier, E., Frachet Bour, A., Baginska, J., Shah, P., Desai, M., Glaab, E., Jäger, C., Haan, S., & Wilmes, P. (June 2016). A study of the molecular mechanisms underlying the response of human colorectal adenomacarcinoma enterocytes to prebiotics and probiotics [Poster presentation]. ISAPP conference.

Glaab, E. (09 May 2016). Integrating prior biological knowledge into omics data analysis [Paper presentation]. Machine Learning Workshop, Oslo, Norway.

Ashrafi, A., Buttini, M., Garcia, P., del Sol Mesa, A., & Glaab, E. (2016). Exploring therapeutic viability of a non-dopaminergic target for Parkinson’s disease. Movement Disorders, 31 (2), 630.
Peer Reviewed verified by ORBi

Kleiderman, S., Sá, J., Teixeira, A., Brito, C., Gutbier, S., Evje, L., Hadera, M., Glaab, E., Henry, M., Agapios, S., Alves, P., Sonnewald, U., & Leist, M. (2016). Functional and phenotypic differences of pure populations of stem cell-derived astrocytes and neuronal precursor cells. Glia, 64 (5), 695-715. doi:10.1002/glia.22954
Peer Reviewed verified by ORBi

Maes, Nowak, G., Caso, J., Leza, J. C., Song, C., Kubera, M., Klein, H., Galecki, P., Noto, C., Glaab, E., Balling, R., & Berk, M. (2016). Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research. Molecular Neurobiology, 53 (5), 2927-2935. doi:10.1007/s12035-015-9183-5
Peer reviewed

Kleiderman, S., Gutbier, S., Tufekci, K. U., Ortega, F., Sá, J. V., Teixeira, A. P., Brito, C., Glaab, E., Berninger, B., Alves, P. M., & Leist, M. (2016). Conversion of non-proliferating astrocytes into neurogenic neural stem cells: control by FGF2 and IFN-gamma. Stem Cells, 34 (12), 2861–2874. doi:10.1002/stem.2483
Peer Reviewed verified by ORBi

Glaab, E. (2016). Modelling gender-specific regulation of tau in Alzheimer’s disease [Paper presentation]. Luxembourg Centre for Systems Biomedicine Annual Donor Thank You Event 2016.

Shah, P., Fritz, J., Glaab, E., Desai, M. S., Greenhalgh, K., Frachet Bour, A., Niegowska, M., Estes, M., Jäger, C., Seguin-Devaux, C., Zenhausern, F., & Wilmes, P. (2016). A microfluidics-based in vitro model of the gastrointestinal human-microbe interface. Nature Communications, 7, 11535. doi:10.1038/ncomms11535
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Casadei, N., Sood, P., Ulrich, T., Kieper, N., Helling, S., May, C., Glaab, E., Chen, J., Nuber, S., Marcus, K., Rapaport, D., Ott, T., Riess, O., Krüger, R., & Fitzgerald, J. (2016). Mitochondrial Defects and Neurodegeneration in Mice Overexpressing Wild Type or G399S Mutant HtrA2. Human Molecular Genetics, 25 (3), 459-71. doi:10.1093/hmg/ddv485
Peer Reviewed verified by ORBi

Allen, G., Amoroso, N., Anghel, C., Balagurusamy, V., Bare, C., Beaton, D., Bellotti, R., Bennett, D., Boehme, K., Caberlotto, L., Campbell, F., Chang, Y.-C., Chen, B., Chen, C.-Y., Chien, T.-Y., Clark, T., Das, S., Davatzikos, C., Deng, J., ... Alzheimer's Disease Neuroimaging Initiative. (2016). Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease. Alzheimer's and Dementia: the Journal of the Alzheimer's Association, 12 (6), 645-653. doi:10.1016/j.jalz.2016.02.006
Peer reviewed

Birck, C., Koncina, E., Heurtaux, T., Glaab, E., Michelucci, A., Heuschling, P., & Grandbarbe, L. (10 November 2015). Transcriptomic analyses of primary astrocytes under TNFα treatment. Genomics Data, 7, 7-11. doi:10.1016/j.gdata.2015.11.005
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Gabel, S., Koncina, E., Dorban, G., Heurtaux, T., Birck, C., Glaab, E., Michelucci, A., Heuschling, P., & Grandbarbe, L. (17 September 2015). Inflammation Promotes a Conversion of Astrocytes into Neural Progenitor Cells via NF-κB Activation. Molecular Neurobiology, 53 (8), 5041-5055. doi:10.1007/s12035-015-9428-3
Peer reviewed

Glaab, E. (2015). Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification. Briefings in Bioinformatics, 1-13. doi:10.1093/bib/bbv044
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Glaab, E. (2015). Building a virtual ligand screening pipeline using free software: a survey. Briefings in Bioinformatics, 1-15. doi:10.1093/bib/bbv037
Peer reviewed

Glaab, E., & Schneider, R. (15 June 2015). Shared alterations in the human brain transcriptome during adult aging and in Parkinson's disease [Poster presentation]. EMBO Symposium on Mechanisms of Neurodegeneration 2015, Heidelberg, Germany.

Glaab, E., & Schneider, R. (February 2015). Comparative pathway and network analysis of brain transcriptome changes during adult aging and in Parkinson's disease. Neurobiology of Disease, 74, 1-13. doi:10.1016/j.nbd.2014.11.002
Peer Reviewed verified by ORBi

Righetti, K., Vu, J. L., Pelletier, S., Vu, B. L., Glaab, E., Lalanne, D., Pasha, A., Patel, R. V., Provart, N., Verdier, J., & Leprince, O. (2015). Inference of longevity-related genes from a robust co-expression network of seed maturation identifies new regulators linking seed storability to biotic defense-related pathways. Plant Cell, 27 (10), 2692-2708. doi:10.1105/tpc.15.00632
Peer Reviewed verified by ORBi

Glaab, E., & Schneider, R. (2015). RepExplore: Addressing technical replicate variance in proteomics and metabolomics data analysis. Bioinformatics, 31 (13), 2235. doi:10.1093/bioinformatics/btv127
Peer reviewed

Jäger, C.* , Glaab, E.* , Michelucci, A.* , Binz, T., Köglsberger, S., Garcia, P., Trezzi, J.-P., Ghelfi, J., Balling, R., & Buttini, M. (2015). The Mouse Brain Metabolome: Region-Specific Signatures and Response to Excitotoxic Neuronal Injury. American Journal of Pathology, 185 (6), 1699-1712. doi:10.1016/j.ajpath.2015.02.016
Peer Reviewed verified by ORBi
* These authors have contributed equally to this work.

Vlassis, N., & Glaab, E. (2015). GenePEN: analysis of network activity alterations in complex diseases via the pairwise elastic net. Statistical Applications in Genetics and Molecular Biology, 14 (2), 221-224. doi:10.1515/sagmb-2014-0045
Peer Reviewed verified by ORBi

Kolodkin, A., Ignatenko, A., Sangar, V., Simeonidis, V., Glaab, E., Peters, B., Brady, N., Price, N., & Balling, R. (October 2014). ROS-management in Parkinson’s disease: Dynamic blue-print domino-based model and design principles study. Dynamic modelling of ROS management and ROS-induced mitophagy [Poster presentation]. GFG Neurogenetics Conference & PD Symposium, Munsbach, Luxembourg.

Glaab, E. (01 October 2014). Integrated bioinformatics analysis of functional omics and GWAS data for neurodegenerative disorders [Paper presentation]. 45th Annual Conference of the German Society for Genetics.

Kolodkin, A., Ignatenko, A., Sangar, V., Glaab, E., Peters, B., Price, N., Brady, N., & Balling, R. (June 2014). Dynamic modelling of ROS management and ROS-induced mitophagy [Poster presentation]. Gordon workshop on Cell Death Mechanisms, West Dover, United States.

Glaab, E., & Schneider, R. (2014). Addressing Technical Replicate Variance in Omics Data Analysis [Poster presentation]. Benelux Bioinformatics Conference 2014.

Fujita, K. A., Ostaszewski, M., Matsuoka, Y., Ghosh, S., Glaab, E., Trefois, C., Crespo, I., Perumal, T. M., Jurkowski, W., Antony, P., Diederich, N., Buttini, M., Kodama, A., Satagopam, V., Eifes, S., del Sol Mesa, A., Schneider, R., Kitano, H., & Balling, R. (2014). Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map. Molecular Neurobiology. doi:10.1007/s12035-013-8489-4
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Heintz, A., May, P., Lebrun, L., Ferrand, J., Trezzi, J.-P., Collignon, S., Wampach, L., Glaab, E., Laczny, C. C., Martins Conde, P., Kaysen, A., Schneider, J., Hiller, K., Hogan, A., Wilmes, P., & de Beaufort, C. (October 2013). Meta-omic Analyses of the Microbiome in a Family Study of Diabetes Mellitus [Poster presentation]. 2nd International Systems Biomedicine Symposium, Belval, Luxembourg.

Ostaszewski, M., Fujita, K., Matsuoka, Y., Ghosh, S., Glaab, E., Trefois, C., Crespo, I., Perumal, T. M., Jurkowski, W., Antony, P., Diederich, N., Buttini, M., Kolodkin, A., Kodama, A., Satagopam, V., Biryukov, M., Eifes, S., del Sol Mesa, A., Schneider, R., ... Balling, R. (09 March 2013). The Parkinson's Disease Map: A Framework for Integration, Curation and Exploration of Disease-related Pathways [Poster presentation]. The 11th International Conference on Alzheimer's & Parkinson's Diseases, Florence, Italy.

Chaiboonchoe, A., Jurkowski, W., Pellet, J., Glaab, E., Kolodkin, A., Raussel, A., Le Béchec, A., Meyniel, L., Ballereau, S., Crespo, I., Ahmed, H., Volpert, V., Lotteau, V., Baliga, N., Hood, L., del Sol, A., Balling, R., & Auffray, C. (2013). Network analysis for systems biology. In A. Prokop & Csukás (Eds.), Springer book in Systems Biology, Vol.1: Systems Biology:, Integrative Biology and Simulation Tools (Springer book in Systems Biology, Vol.1). Springer. doi:10.1007/978-94-007-6803-1
Peer reviewed

Muller, E., Glaab, E., May, P., Vlassis, N., & Wilmes, P. (2013). Condensing the omics fog of microbial communities. Trends in Microbiology, 21 (7), 325–333. doi:10.1016/j.tim.2013.04.009
Peer reviewed

Vlassis, N., & Glaab, E. (2013). Network deregulation analysis in complex diseases via the pairwise elastic net. In Proc 8th BeNeLux Bioinformatics Conference. doi:10.1515/sagmb-2014-0045
Peer reviewed

Ballereau, S., Glaab, E., Kolodkin, A., Chaiboonchoe, A., Biryukov, M., Vlassis, N., Ahmed, H., Pellet, J., Baliga, N., Hood, L., Schneider, R., Balling, R., & Auffray, C. (2013). Functional Genomics, Proteomics, Metabolomics and Bioinformatics for Systems Biology. In A. Prokop & B. Csukás (Eds.), Systems Biology: Integrative Biology and Simulation Tools. Springer. doi:10.1007/978-94-007-6803-1_1
Peer reviewed

Chaiboonchoe, A., Jurkowski, W., Pellet, J., Glaab, E., Kolodkin, A., Raussel, A., Le Béchec, A., Ballereau, S., Meyniel, L., Crespo, I., Ahmed, H., Volpert, V., Lotteau, V., Baliga, N., Hood, L., Sol, A. D., Balling, R., & Auffray, C. (2013). On different aspects of network analysis in systems biology. Systems Biology, 1, 181-207. doi:10.1007/978-94-007-6803-1_6
Peer reviewed

Trefois, C., Fujita, A. K., Ostaszewski, M., Matsuoka, Y., Ghosh, S., Glaab, E., Crespo, I., Perumal, T. M., Jurkowski, W., Antony, P., Diederich, N., Buttini, M., Kodama, A., Satagopam, V., Eifes, S., del Sol Mesa, A., Schneider, R., Kitano, H., & Balling, R. (August 2012). Constructing a comprehensive map of Parkinson’s disease to elucidate underlying mechanisms of its multifaceted molecular pathology [Poster presentation]. The 13th International Conference on Systems Biology.

Glaab, E., Bacardit, J., Garibaldi, J. M., & Krasnogor, N. (2012). Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. PLoS ONE, 7 (7), 39932 - 39932. doi:10.1371/journal.pone.0039932
Peer Reviewed verified by ORBi

Glaab, E., Baudot, A., Krasnogor, N., Schneider, R., & Valencia, A. (2012). EnrichNet: network-based gene set enrichment analysis. Bioinformatics, 28 (18), 451-i457. doi:10.1093/bioinformatics/bts389
Peer reviewed

Glaab, E., & Schneider, R. (2012). PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data. Bioinformatics, 446-447. doi:10.1093/bioinformatics/btr656
Peer reviewed

Bassel, G. W., Glaab, E., Marquez, J., Holdsworth, M. J., & Bacardit, J. (2011). Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets. Plant Cell, 1-17. doi:10.1105/tpc.111.088153
Peer Reviewed verified by ORBi

Gardner, D. S., Rhodes, P., Karamitri, A., Glaab, E., & Rhind, S. M. (2011). A low protein diet during early gestation in sheep detrimentally impacts hepatic glucose metabolism in the adult offspring. In Proceedings of the Nutrition Society 2011 (pp. 196). Cambridge University Press. doi:10.1017/S0029665111002473
Peer reviewed

Habashy, H. O., Powe, D. G., Glaab, E., Ball, G., Spiteri, I., Krasnogor, N., Garibaldi, J. M., Rakha, E. A., Green, A. R., Caldas, C., & Ellis, I. O. (2011). RERG (Ras-like, oestrogen-regulated, growth-inhibitor) expression in breast cancer: a marker of ER-positive luminal-like subtype. Breast Cancer Research and Treatment, 128 (2), 315-326. doi:10.1007/s10549-010-1073-y
Peer reviewed

Bassel, G. W., Lanc, H., Glaab, E., Gibbs, D. J., Gerjets, T., Krasnogor, N., Bonner, A. J., Holdsworth, M. J., & Provart, N. J. (2011). A genome-wide network model capturing seed germination reveals co-ordinated regulation of plant cellular phase transitions. Proceedings of the National Academy of Sciences of the United States of America, 108 (23), 9709-9714. doi:10.1073/pnas.1100958108
Peer Reviewed verified by ORBi

Glaab, E., Baudot, A., Krasnogor, N., & Valencia, A. (2010). Extending pathways and processes using molecular interaction networks to analyse cancer genome data. BMC Bioinformatics, 11 (1), 597-597. doi:10.1186/1471-2105-11-597
Peer Reviewed verified by ORBi

Glaab, E., Garibaldi, J. M., & Krasnogor, N. (2010). VRMLGen: An R package for 3D Data Visualization on the Web. Journal of Statistical Software, 36 (8), 1-18. doi:10.18637/jss.v036.i08
Peer Reviewed verified by ORBi

Glaab, E., Baudot, A., Krasnogor, N., & Valencia, A. (2010). TopoGSA: network topological gene set analysis. Bioinformatics, 26 (9), 1271-1272. doi:10.1093/bioinformatics/btq131
Peer reviewed

Glaab, E., Garibaldi, J. M., & Krasnogor, N. (2010). Learning pathway-based decision rules to classify microarray cancer samples. In German Conference on Bioinformatics 2010, Lecture Notes in Informatics (LNI) (pp. 123-134).
Peer reviewed

Habashy, H. O., Powe, D. G., Ball, G., Glaab, E., Soria, D., Garibaldi, J., Krasnogor, N., Green, A. R., Caldas, C., & Ellis, I. O. (2010). Luminal-like oestrogen receptor-positive breast cancer: identification of prognostic biological subclasses. European Journal of Cancer Supplements, 8 (3), 91. doi:10.1016/S1359-6349(10)70143-9
Peer reviewed

Glaab, E., Clutterbuck, L., Bacardit, J., Wood, A. T., & Mobasheri, A. (2010). Combining chondrocyte gene expression, literature mining and pathway/network analysis to extract biological insights from small-scale microarray data. Osteoarthritis and Cartilage, 18 (2), 169. doi:10.1016/S1063-4584(10)60411-6
Peer Reviewed verified by ORBi

Glaab, E., Garibaldi, J. M., & Krasnogor, N. (2009). ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization. BMC Bioinformatics, 10 (1), 358-358. doi:10.1186/1471-2105-10-358
Peer Reviewed verified by ORBi

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