Enrico Glaab
Enrico Glaab, Ph.D.


General research interests
My main research interest is the development and application of statistical learning, pathway and network analysis algorithms on biological data from high-throughput experiments using combinatorial optimisation. Currently, I am working on the integrative machine learning analysis of omics data from disease-related case-control studies, focussing on biomarker development for the neurodegenerative disorders Alzheimer's and Parkinson's (e.g. as part of the National Centre of Excellence in Research on Parkinson's Disease, NCER-PD).

In recent years, I have built various web-servers for online analysis of biological data, including:
  • ArrayMining.net, a web-application for microarray data analysis,
  • EnrichNet, a web-service for network-based gene and protein set enrichment analysis,
  • TopoGSA, a web-based software for comparative network topological analysis of genes/proteins,
  • PathExpand, a web-application to extend cellular pathway definitions using molecular networks,
  • VRMLGen, an R-package and web-application for 3D visualization of biological data,
  • PathVar, a web-based software for pathway-based microarray sample classification and clustering,
  • RepExplore, a web-service for the analysis of proteomics and metabolomics data with technical replicates.
See also our group's Bioinformatics Software Portal for more details and further software tools.
Applications from prospective PostDocs in bioinformatics are welcome. Students interested in pursuing a master's degree at the interface of bioinformatics and experimental biology may want to consider our programme Master in Integrated Systems Biology.

Publications (All articles in BibTeX format)

  1. 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 full-text online [BibTeX]
  2. 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 Parkinsons Disease, Movement Disorders (2025), in press (doi:10.1002/mds.30223) (full-text online) [BibTeX]
  3. M. Ali, P. Garcia, L.P. Lunkes, A. Sciortino, M. Thomas, T. Heurtaux, K. Grzyb, R. Halder, A. Skupin, L. Buée, D. Blum, M. Buttini, E. Glaab, Temporal Transcriptomic Changes in the THY-Tau22 Mouse Model of Tauopathy Display Cell Type- and Sex-Specific Differences, Acta Neuropathologica Communications (2025), 13, 93 full-text online [BibTeX]
  4. T. Hähnel, T. Raschka, J. Klucken, E. Glaab, J.-C. Corvol, B.H. Falkenburger, H. Fröhlich, Predictive modeling to uncover Parkinsons disease characteristics that delay diagnosis, npj Parkinson's Disease (2025), 11, 64 (full-text online) [BibTeX]
  5. R.T.J. Loo, F. Nasta, M. Macchi, A. Baudot, F. Burstein, R. Bove, M. Greve, H. Fröhlich, S. Khalid, A. Küderle, S.L. Moore, V. Storms, J. Torous, E. Glaab, Recommendations For Successful Development And Implementation Of Digital Health Technology Tools, Journal of Medical Internet Research (2025), in press [BibTeX]
  6. A. Zagare, J. Kurlovics, C. Almeida, D. Ferrante, D. Frangenberg, A. Vitali, G. Gomez-Giro, C. Jäger, P. Antony, R. Halder, R. Krüger, E. Glaab, E. Stalidzans, G. Arena, J.C. Schwamborn, Insulin resistance compromises midbrain organoid neuronal activity and metabolic efficiency predisposing to Parkinson's disease pathology, J Tissue Eng (2025), in press, doi:10.1177/20417314241295928 (full-text online) [BibTeX]
  7. 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 Parkinsons disease, npj Digital Medicine (2024), 7, 235 (full-text online) [BibTeX]
  8. M. Ali, P. Garcia, L.P. Lunkes, A. Sciortino, M. Thomas, T. Heurtaux, K. Grzyb, R. Halder, D. Coowar, A. Skupin, L. Buée, D. Blum, M. Buttini, E. Glaab, Single cell transcriptome analysis of the THY-Tau22 mouse model of Alzheimer's disease reveals sex-dependent dysregulations, Cell Death Discovery (2024), 10, 119 (full-text online) [BibTeX]
  9. H. Scheiblich, F. Eikens, L. Wischhof, S. Opitz, K. Jüngling, C. Cserép, S.V. Schmidt, J. Lambertz, T. Bellande, B. Pósfai, C. Geck, J. Spitzer, A. Odainic, S. Castro-Gomez, S. Schwartz, I. Boussaad, R. Krüger, E. Glaab, D.A. Di Monte, D. Bano, Á. Dénes, E. Latz, R. Melki, H.C. Pape, M.T. Heneka, Microglia rescue neurons from aggregate-induced neuronal dysfunction and death through tunneling nanotubes, Neuron (2024), 112(18):3106 (full-text online) [BibTeX]
  10. S. Le Bars, E. Glaab, Single-Cell Cortical Transcriptomics Reveals Common and Distinct Changes in Cell-Cell Communication in Alzheimer's and Parkinson's Disease, Molecular Neurobiology (2024), 10.1007/s12035-024-04419-7 (full-text online) [BibTeX]
  11. H. Feng, D. Pogorelov, S. Bode, X. He, J. Ramiro-Garcia, F. Hedin, W. Ammerlaan, M. Konstantinou, C. Capelle, N. Zeng, A. Poli, O. Domingues, G. Montamat, O. Hunewald, S. Ciré, A. Baron, J. Longworth, L. Neuberger-Castillo, D. Revets, L. Guyonnet, A. Demczuk, S. Delhalle, J. Zimmer, V. Benes, F. Codreanu-Morel, C. Lehners-Weber, I. Weets, P. Alper, D. Brenner, J. Gutermuth, C. Guérin, M. Morisset, F. Hentges, R. Schneider, M. Shamji, F. Betsou, P. Wilmes, E. Glaab, J. Goncalves, A. Cosma, M. Bazon, I. Casper, L. Klimek, M. Ollert, Multiomics approaches disclose very-early molecular and cellular switches during insect-venom allergen-specific immunotherapy: an observational study, Nature Communications (2024), 15, 10266 (full-text online) [BibTeX]
  12. 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 [BibTeX]
  13. 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 (full-text online) [BibTeX]
  14. G. Arena, Z. Landoulsi, D. Grossmann, T. Payne, A. Vitali, S. Delcambre, A. Baron, P. Antony, I. Boussaad, D.R. Bobbili, A.A.K. Sreelatha, L. Pavelka, C. Klein, P. Seibler, E. Glaab, T. Foltynie, O. Bandmann, M. Sharma, R. Krüger, P. May, A. Grünewald, Polygenic risk scores validated in patient-derived cells stratify for mitochondrial subtypes of Parkinson's disease, Annals of Neurology (2024), 96, 1 (full-text online) [BibTeX]
  15. R.T.J. Loo, O. Tsurkalenko, J. Klucken, G. Mangone, F. Khoury, M. Vidailhet, J.-C. Corvol, R. Krüger, E. Glaab, Levodopa-induced dyskinesia in Parkinson's disease: Insights from cross-cohort prognostic analysis using machine learning, Parkinsonism & Related Disorders (2024), 126, 107054 (full-text online) [BibTeX]
  16. A. Zagare, A. Hemedan, C. Almeida, D. Frangenberg, G. Gomez-Giro, P. Antony, R. Halder, R. Krüger, E. Glaab, M. Ostaszewski, G. Arena, J.C. Schwamborn, Insulin Resistance Is a Modifying Factor for Parkinson's Disease, Movement Disorders (2024), 40, 1 (full-text online) [BibTeX]
  17. L. Pavelka, A. Rauschenberger, A. Hemedan, M. Ostaszewski, E. Glaab, R. Krüger, Converging peripheral blood miRNA profiles in Parkinsons disease and progressive supranuclear palsy, Brain Communications (2024), 6, 3 [BibTeX]
  18. P. Kaya, E. Schaffner-Reckinger, G.B. Manoharan, V. Vukic, A. Kiriazis, M. Ledda, M. Burgos, K. Pavic, A. Gaigneaux, E. Glaab, D.K. Abankwa, An improved PDE6D inhibitor combines with Sildenafil to inhibit KRAS-mutant cancer cell growth, Journal of Medicinal Chemistry (2024), 67, 11 [BibTeX]
  19. T. Hähnel, T. Raschka, S. Sapienza, J. Klucken, E. Glaab, J.-C. Corvol, B. Falkenburger, H. Fröhlich Progression subtypes in Parkinson's disease identified by a data driven multi cohort analysis, npj Parkinson's Disease (2024), 10, 95 [BibTeX]
  20. P. Garcia, R. Banzi, V. Fosse, C. Gerardi, E. Glaab, J.M. Haro, E. Oldoni, R. Porcher, J. Subirana-Mirete, C. Superchi, J. Demotes, The PERMIT guidelines for designing and implementing all stages of personalised medicine research, Scientific Reports (2024), 14, 27894 (full-text online) [BibTeX]
  21. A. Rauschenberger, Z. Landoulsi, M. van de Wiel, E. Glaab, Penalised regression with multiple sources of prior effects, Bioinformatics (2023), 39, 12 (full-text online) [BibTeX]
  22. A. Rauschenberger, E. Glaab, Predicting Dichotomised Outcomes from High-Dimensional Data in Biomedicine, Journal of Applied Statistics (2023), 51, 9 (full-text online) [BibTeX]
  23. L. C. Tranchevent, R. Halder, E. Glaab, Systems level analysis of sex-dependent gene expression changes in Parkinson's disease, npj Parkinson's Disease (2023), 9, 8 (full-text online) [BibTeX]
  24. A. Zagare, G. Preciat, S. L. Nickels, X. Luo, A. S. Monzel, G. Gomez-Giro, G. Robertson, C. Jaeger, J. Sharif, H. Koseki, N. J. Diederich, E. Glaab, R. M. T. Fleming, J. C. Schwamborn, Omics data integration suggests a potential idiopathic Parkinson's disease signature, Communications Biology (2023), 6, 1 (full-text online) [BibTeX]
  25. I. Rosety, A. Zagare, C. Saraiva, S. Nickels, P. Antony, C. Almeida, E. Glaab, R. Halder, S. Velychko, T. Rauen, H. R. Schöler, S. Bolognin, T. Sauter, J. Jarazo, R. Krüger, J. C. Schwamborn, Impaired neuron differentiation in GBA-associated Parkinson's disease is linked to cell cycle defects in organoids, npj Parkinson's Disease (2023), 9, 166 (full-text online) [BibTeX]
  26. L. Pavelka, R. Rawal, S. Ghosh, C. Pauly, L. Pauly, A.-M. Hanff, P. L. Kolber, S. R. Jónsdóttir, D. Mcintyre, K. Azaiz, E. Thiry, L. Vilasboas, E. Soboleva, M. Giraitis, O. Tsurkalenko, S. Sapienza, N. Diederich, J. Klucken, E. Glaab, G. A. Aguayo, E. R. Jubal, M. Perquin, M. Vaillant, P. May, M. Gantenbein, V. P. Satagopam, R. Krüger, Luxembourg Parkinson's study - comprehensive baseline analysis of Parkinson's disease and atypical parkinsonism, Frontiers in Neurology (2023), 14, 1330321 (full-text online) [BibTeX]
  27. J. Schimunek, P. Seidl, K. Elez, T. Hempel, T. Le, F. Noé, S. Olsson, ..., E. Glaab, et al. A community effort in SARS-CoV-2 drug discovery, Molecular Informatics (2023), 43, 1 (full-text online) [BibTeX]
  28. L. Khachatryan, Y. Xiang, A. Ivanov, E. Glaab, G. Graham, I. Granata, M. Giordano, L. Maddalena, M. Piccirillo, I. Manipur, G. Baruzzo, M. Cappellato, B. Avot, A. Stan, J. Battey, G. Lo Sasso, S. Boue, N. V. Ivanov, M. C. Peitsch, J. Hoeng, L. Falquet, B. Di Camillo, M. R. Guarracino, V. Ulyantsev, N. Sierro, C. Poussin, Results and lessons learned from the sbv IMPROVER Metagenomics Diagnostics for Inflammatory Bowel Disease Challenge, Scientific Reports (2023), 13, 6303 (full-text online) [BibTeX]
  29. T. Bergquist, T. Schaffter, Y. Yan, T. Yu, J. Prosser, J. Gao, G. Chen, . Charzewski, Z. Nawalany, I. Brugere, R. Retkute, A. Prusokas, Y. Choi, S. Lee, J. Choe, S. Kim, J. Kang, S. D. Mooney, J. Guinney, A. Lee, A. Salehzadeh-Yazdi, A. Basu, A. Belouali, A.-K. Becker, A. Israel, B. Winter, C. Vega Moreno, C. Kurz, D. Waltemath, D. Schweinoch, E. Glaab, G. Luo, H. U. Zacharias, H. Qiao, K. A. Stephens, L. Kaderali, L. R. Varshney, M. Vollmer, M.-T. Pandi, M. L. Gunn, M. Yetisgen, N. Nath, N. Hammarlund, O. Müller-Stricker, P. Togias, P. J. Heagerty, P. Muir, P. Banda, R. Henkel, S. Madgi, S. Gupta, S. Kannattikuni, S. Sarhadi, S. Omar, S. Wang, S. Ghosh, S. Neumann, S. Simm, S. Madhavan, T. V. Yu, V. Satagopam, V. Pejaver, Y. Gupta, Y. Choi., Evaluation of crowdsourced mortality prediction models as a framework for assessing artificial intelligence in medicine, J Am Med Inform Assoc (2023), 31, 1 (full-text online) [BibTeX]
  30. P. Mulica, C. Venegas, Z. Landoulsi, K. Badanjak, S. Delcambre, M. Tziortziou, S. Hezzaz, J. Ghelfi, S. Smajic, J. Schwamborn, R. Krüger, P. Antony, P. May, E. Glaab, A. Grünewald, S. L. Pereira, Comparison of two protocols for the generation of iPSC-derived human astrocytes, Biological Procedures Online (2023), 25, 26 (full-text online) [BibTeX]
  31. S. K. Sieberts, H. Borzymowski, Y. Guan, Y. Huang, A. Matzner, A. Page, I. Bar-Gad, B. Beaulieu-Jones, Y. El-Hanani, J. Goschenhofer, M. Javidnia, M. S. Keller, Y.-C. Li, M. Saqib, G. Smith, A. Stanescu, C. S. Venuto, R. Zielinski, BEAT-PD DREAM Challenge Consortium, A. Jayaraman, L. J. W. Evers, L. Foschini, A. Mariakakis, G. Pandey, N. Shawen, P. Synder, L. Omberg, Developing better digital health measures of Parkinson's disease using free living data and a crowdsourced data analysis challenge, PLOS Digital Health (2023), 2(3), e0000208 (full-text online) [BibTeX]
  32. M. Ali, O. U. Huarte, T. Heurtaux, P. Garcia, B. P. Rodriguez, K. Grzyb, R. Halder, A. Skupin, M. Buttini, E. Glaab, Single-cell transcriptional profiling and gene regulatory network modeling in Tg2576 mice reveal gender-dependent molecular features preceding Alzheimer-like pathologies, Molecular Neurobiology (2022), 61:541 (full-text online) [BibTeX]
  33. A. Rauschenberger, E. Glaab, Predicting correlated outcomes from molecular data, Bioinformatics (2021), 37(21), 3889–3895 (full-text online) [BibTeX]
  34. E. Glaab, G. B. Manoharan, D. Abankwa, 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 (2021), 61(8), 4082–4096 (doi:10.1021/acs.jcim.1c00258, full-text online) [BibTeX]
  35. M. Ostaszewski, A. Niarakis, A. Mazein, I. Kuperstein, R. Phair, A. Orta-Resendiz, V. Singh, S. Aghamiri, M. Acencio, E. Glaab, A. Ruepp, G. Fobo, C. Montrone, B. Brauner, G. Frishman, L. M. Gomez, J. Somers, M. Hoch, S. K. Gupta, J. Scheel, H. Borlinghaus, T. Czauderna, F. Schreiber, A. Montagud, M. P. de León, A. Funahashi, Y. Hiki, N. Hiroi, T. Yamada, A. Dräger, A. Renz, M. Naveez, Z. Bocksei, F. Messina, D. Böringen, L. Fergusson, M. Conti, M. Rameil, V. Nakonecnij, J. Vanhoefer, L. Schmiester, M. Wang, E. Ackerman, J. Shoemaker, J. Zucker, K. Oxford, J. Teuton, E. Kocakaya, G. Summak, K. Hanspers, M. Kutmon, S. Coort, L. Eijssen, F. Ehrhart, D. A. B. Rex, D. Slenter, M. Martens, N. Pham, R. Haw, B. Jassal, L. Matthews, M. Orlic-Milacic, A. Senff-Ribeiro, K. Rothfels, V. Shamovsky, R. Stephan, C. Sevilla, T. Varusai, J. Ravel, R. Fraser, V. Ortseifen, S. Marchesi, P. Gawron, E. Smula, L. Heirendt, V. Satagopam, G. Wu, A. Riutta, M. Golebiewski, S. Owen, C. Goble, X. Hu, R. Overall, D. Maier, A. Bauch, J. Bachman, B. Gyori, C. Vega, V. Groues, M. Vazquez, P. Porras, L. Licata, M. Iannuccelli, F. Sacco, A. Nesterova, A. Yuryev, A. de Waard, D. Turei, A. Luna, O. Babur, S. Soliman, A. Valdeolivas, M. Esteban, M. Peña-Chilet, K. Rian, T. Helikar, B. L. Puniya, D. Modos, A. Treveil, M. Olbei, B. De Meulder, S. Ballereau, A. Dugourd, A. Naldi, V. Noel, L. Calzone, C. Sander, E. Demir, T. Korcsmaros, T. Freeman, F. Augé, J. Beckmann, J. Hasenauer, O. Wolkenhauer, E. Wilighagen, A. Pico, C. Evelo, M. Gillespie, L. Stein, H. Hermjakob, P. D'Eustachio, J. Saez-Rodriguez, J. Dopazo, A. Valencia, H. Kitano, E. Barillot, C. Auffray, R. Balling, R. Schneider, COVID-19 Disease Map Community COVID-19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms, Molecular Systems Biology (2021), 17(10), e10378 (full-text online) [BibTeX]
  36. V. Priesemann, R. Balling, S. Bauer, P. Beutels, A. v, S. Cuschieri, T. Czypionka, U. Dumpis, E. Glaab, E. Grill, P. Hotulainen, E. N. Iftekhar, J. Krutzinna, C. Lionis, H. Machado, C. Martins, M. McKee, G. N. Pavlakis, M. Perc, E. Petelos, M. Pickersgill, B. Prainsack, E. Schernhammer, E. Szczurek, S. Tsiodras, S. Van Gucht, P. Willeit, The benefits of low COVID-19 incidence in Europe, The Lancet (2021), 398(10303), 838-839 (full-text online) [BibTeX]
  37. L. Pavelka, A. Rauschenberger, Z. Landoulsi, S. Pachchek, T. Marques, C. P. C. Gomes, E. Glaab, P. May, R. Krüger, NCER-PD Consortium 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 (2022), 12, 8 [BibTeX]
  38. L. Pavelka, A. Rauschenberger, Z. Landoulsi, S. Pachchek, P. May, E. Glaab, Krüger R, Age at onset as stratifier in idiopathic Parkinson's disease - effect of ageing and polygenic risk score on clinical phenotypes, npj Parkinson's Disease (2022), 8, 1 [BibTeX]
  39. R. Diaz-Uriarte, E. Gómez de Lope, R. Giugno, H. Fröhlich, P. V. Nazarov, I. A. Nepomuceno-Chamorro, A. Rauschenberger, E. Glaab, Ten Quick Tips for Biomarker Discovery and Validation Analyses Using Machine Learning, PLoS Computational Biology (2022), 18, 8, e1010357 (full-text online) [BibTeX]
  40. C. Pauly, E. Glaab, M. Hansen, C. Martin-Gallausiaux, M. Ledda, T. Marques, P. Wilmes, R. Krüger, NCER-PD consortium, Parkinson's Disease progression, resilience and inflammation markers during the COVID-19 pandemic, Movement Disorders (2022), 37, 11 [BibTeX]
  41. P. Mencke, Z. Hanss, J. Jarazo, F. Massart, A. Rybicki, E. Petkovski, E. Glaab, I. Boussaad, V. Bonifati, J. Christian, W. Mandemakers, R. Krüger, Generation of isogenic control DJ-1-delP GC13 for the genetic Parkinson's disease-patient derived iPSC line DJ-1-delP (LCSBi008-A-1), Stem Cell Research (2022), 62, 102815 (full-text online) [BibTeX]
  42. P. Garcia, W. Wemheuer, O. U. Huarte, A. Michelucci, A. Masuch, S. Brioschi, A. Weihofen, E. Koncina, D. Coowar, T. Heurtaux, E. Glaab, R. Balling, C. Sousa, T. Kaoma, N. Nicot, T. Pfander, W. Schulz-Schaeffer, A. Allouche, N. Fischer, K. Biber, M. Mittelbronn, M. Ostaszewski, K. J. Schmit, M. Buttini, Neurodegeneration and neuroinflammation are linked, but independent of a-synuclein inclusions, in a seeding/spreading mouse model of Parkinson's disease, Glia (2022), 70(5), 935-960 (full-text online) [BibTeX]
  43. M. Balta, O. Schreurs, R. Halder, T. Kuntziger, F. Saetre, I. J. S. Blix, E. Bækkevold, E. Glaab, K. Schenck RvD1n-3 DPA Downregulates the Transcription of Pro-Inflammatory Genes in Oral Epithelial Cells and Reverses Nuclear Translocation of Transcription Factor p65 after TNF-a Stimulation, International Journal of Molecular Sciences (2022), in press (full-text online) [BibTeX]
  44. M. Balta, O. Schreurs, T. Hansen, J. Tungen, A. Vik, E. Glaab, T. Kuntziger, K. Schenck, E. Bækkevold, I. J. S. Blix, Expression and function of Resolvin D1n-3 DPA receptors in oral epithelial cells, European Journal of Oral Sciences (2022), in press (full-text online) [BibTeX]
  45. E. Glaab, A. Rauschenberger, R. Banzi, C. Gerardi, P. Garcia, J. Demotes-Mainard, and the PERMIT Group, Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review, BMC Open (2021), 11, e053674 (full-text online) [BibTeX]
  46. E. N. Iftekhar, V. Priesemann, R. Balling, S. Bauer, P. Beutels, A. C. Valdez, S. Cuschieri, T. Czypionka, U. Dumpis, E. Glaab, E. Grill, C. Hanson, P. Hotulainen, P. Klimek, M. Kretzschmar, T. Krüger, J. Krutzinna, N. Low, H. Machado, C. Martins, M. McKee, S. Bernd, A. Nassehi, M. Perc, E. Petelos, M. Pickersgill, B. Prainsack, J. Rocklöv, E. Schernhammer, A. Staines, E. Szczurek, S. Tsiodras, S. Van Gucht, P. Willeit, A look into the future of the COVID-19 pandemic in Europe: an expert consultation, The Lancet Regional Health Europe (2021), 8, 100185 (full-text online) [BibTeX]
  47. H. Fröhlich, N. Bontridder, D. Petrovska-Delacréta, E. Glaab, F. Kluge, M. Yacoubi, M. M. Valero, J. Corvol, B. Eskofier, J. Van Gyseghem, S. Lehericy, J. Winkler, J. Klucken Leveraging the Potential of Digital Technology for Better Individualized Treatment of Parkinson’s Disease, Frontiers in Neurology (2022), 13, 788427 (full-text online) [BibTeX]
  48. T. Czypionka, E. Iftekhar, B. Prainsack, V. Priesemann, S. Bauer, A. C. Valdez, S. Cuschieri, E. Glaab, E. Grill, J. Krutzinna, C. Lionis, H. Machado, C. Martins, G. Pavlakis, M. Perc, E. Petelos, M. Pickersgill, A. Skupin, E. Schernhammer, E. Szczurek, S. Tsiodras, P. Willeit, P. Wilmes, The benefits, costs and feasibility of a low incidence COVID-19 strategy, The Lancet Regional Health - Europe (2021), 13, 100294 (full-text online) [BibTeX]
  49. K. Badanjak, P. Mulica, S. Smajic, S. Delcambre, L. Tranchevent, N. Diederich, T. Rauen, J. Schwamborn, E. Glaab, S. Cowley, P. Antony, S. Pereira, C. Venegas, A. Grünewald iPSC-Derived Microglia as a Model to Study Inflammation in Idiopathic Parkinson's Disease, Frontiers in cell and developmental biology (2021), 9, 740758 (full-text online) [BibTeX]
  50. I. Boussaad, C. D. Obermaier, Z. Hanss, D. R. Bobbili, S. Bolognin, E. Glaab, K. Wolynska, N. Weisschuh, L. De Conti, C. May, F. Giesert, D. Grossmann, A. Lambert, S. Kirchen, M. Biryukov, L. F. Burbulla, F. Massart, J. Bohler, G. Cruciani, B. Schmid, A. Kurz-Drexler, P. May, S. Duga, C. Klein, J. C. Schwamborn, K. Marcus, D. Woitalla, D. M. Vogt Weisenhorn, W. Wurst, M. Baralle, D. Krainc, T. Gasser, B. Wissinger, R. Krüger, A patient-based model of RNA mis-splicing uncovers treatment targets in Parkinson's disease, Science Translational Medicine (2020), 12, 560 (original article) [BibTeX]
  51. J. Imm, E. Pishva, M. Ali, T. L. Kerrigan, A. Jeffries, J. Burrage, E. Glaab, E. L. Cope, K. M. Jones, N. D. Allen, K. Lunnon, Characterization of DNA Methylomic Signatures in Induced Pluripotent Stem Cells During Neuronal Differentiation, Frontiers in Cell and Developmental Biology (2021), 9, 647981 (original article) [BibTeX]
  52. C. Giovagnoni, M. Ali, L. M. T. Eijssen, R. Maes, K. Choe, M. Mulder, J. Kleinjans, A. del Sol, E. Glaab, D. Mastroeni, E. Delvaux, P. Coleman, M. Losen, E. Pishva, P. M. Martinez, D. L. A. van den Hove, Altered sphingolipid function in Alzheimer's disease; a gene regulatory network approach, Neurobiology of Aging (2021), 102, 178-187 (original article) [BibTeX]
  53. S. Sieberts, J. Schaff, M. Duda, B. Pataki, M. Sun, P. Snyder, J. Daneault, F. Parisi, G. Costante, U. Rubin, P. Banda, Y. Chae, E. Neto, E. Dorsey, Z. Aydin, A. Chen, L. Elo, C. Espino, E. Glaab, E. Goan, F. Golabchi, Y. Görmez, M. Jaakkola, J. Jonnagaddala, R. Klén, D. Li, C. McDaniel, D. Perrin, N. Rad, T. Perumal, E. Rainaldi, S. Sapienza, P. Schwab, N. Shokhirev, M. Venäläinen, G. Vergara-Diaz, Y. Zhang, Y. Wang, The Parkinson's Disease Digital Biomarker Challenge Consortium, Y. Guan, D. Brunner, P. Bonato, L. Mangravite, L. Omberg, Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge, npj Digital Medicine (2021), 4, 53 (original article) [BibTeX]
  54. E. Glaab, J.P. Trezzi, A. Greuel, C. Jäger, Z. Hodak, A. Drzezga, L. Timmermann, M. Tittgemeyer, N. J. Diederich, C. Eggers, Integrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease, Neurobiology of Disease (2019), 124, 555-562 (doi: 10.1038/s41380-018-0091-8, full-text online) [BibTeX]
  55. A. Greuel, J. P. Trezzi, E. Glaab, M. C. Ruppert, F Maier, C. Jäger, Z. Hodak, L. Timmermann, K. Hiller, M. Tittgemeyer, A. Drzezga, N. Diederich, C. Eggers, GBA variants in Parkinson's disease: clinical, metabolomic and multimodal neuroimaging phenotypes, Movement Disorders (2020), 35(12), 2201-2210 (doi: 10.1002/mds.28225, fulltext-online) [BibTeX]
  56. J. Tanevski, T. Nguyen, B. Truong, N. Karaiskos, M. Eren, X. Zhang, C. Shu, Y. Hu, H. V. V. Pham, X. Li, T. Le, A. Tarca, G. Bhatti, R. Romero, N. Karathanasis, P. Loher, Y. Chen, Z. Ouyang, D. Mao, Y. Zhang, M. Zand, J. Ruan, C. Hafemeister, P. Qiu, D. Tran, T. Nguyen, A. Gabor, T. Yu, E. Glaab, R. Krause, P. Banda, G. Stolovitzky, N. Rajewsky, J. Saez-Rodriguez, Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics, Life Science Alliance (2020), 3(11), e202000867 (original article) [BibTeX]
  57. D. M. Hendrickx, P. Garcia, A. Ashrafi, A. Sciortino, K. J. Schmit, H. Kollmus, N. Nicot, T. Kaoma, L. Vallar, M. Buttini, E. Glaab, A new synuclein-transgenic mouse model for early Parkinson's reveals molecular features of preclinical disease, Molecular Neurobiology (2020), 58, 576-602 [BibTeX]
  58. A. Rauschenberger, E. Glaab, M. van de Wiel, Predictive and interpretable models via the stacked elastic net, Bioinformatics (2021), 37(14), 2012–2016 (original article) [BibTeX]
  59. S. Acharya, A. Salgado-Somoza, F. M. Stefanizzi, A. I. Lumley, L. Zhang, E. Glaab, P. May, Y. Devaux, Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease, International Journal of Molecular Sciences (2020), 21(18), 6513 (original article) [BibTeX]
  60. D. M. Hendrickx, E. Glaab, Comparative transcriptome analysis of Parkinson’s disease and Hutchinson-Gilford progeria syndrome reveals shared susceptible cellular network processes, BMC Medical Genomics (2020), 13, 114 (original article) [BibTeX]
  61. M. Ganzinger, E. Glaab, J. Kerssemakers, S. Nahnsen, U. Sax, N. Sarah, M. Schapranow, T. Tiede, Biomedical and Clinical Research Data Management, in Systems Medicine - Integrative, Qualitative and Computational Approaches (2021), 3, 532-543 (online version) [BibTeX]
  62. M. J. DeBenedictis, Y. Gindzin, E. Glaab. B. Anand-Apte, A novel TIMP3 mutation associated with a retinitis pigmentosa-like phenotype, Ophthalmic Genetics (2020), Vol. 41, No. 5, pp. 480 (original article) [BibTeX]
  63. F. Baldini, J. Hertel, E. Sandt, C. C. Thinnes, L. Neuberger-Castillo, L.Pavelka, F. Betsou, R. Krüger, I. Thiele, NCER-PD Consortium, et al., Parkinson's disease-associated alterations of the gut microbiome predict disease-relevant changes in metabolic functions, BMC Biology (2020), Vol. 18, No. 1, pp. 1 (full-text online) [BibTeX]
  64. J. Hertel, A. Harms, A. Heinken, F. Baldini, C. Thinnes, E. Glaab, D. Vasco, M. Pietzner, I. Stewart, N. Wareham, C. Langenberg, C. Trenkwalder, R. Krüger, T. Hankemeier, R. Fleming, B. Mollenhauer, I. Thiele, Integrated Analyses of Microbiome and Longitudinal Metabolome Data Reveal Microbial-Host Interactions on Sulfur Metabolism in Parkinson’s Disease, Cell Reports (2019), Vol. 29, No. 7, pp. 1767 (full-text online) [BibTeX]
  65. Z. Zhang, P. P. Jung, V. Grouès, P. May, C. Linster, E. Glaab, Web-based quantitative trait locus linkage analysis and bulk segregant analysis of yeast sequencing data, GigaScience (2019), Vol. 8, No. 6, pp. 1-18 (full-text online) [BibTeX]
  66. S. L. Nickels, J. Walter, S. Bolognin, D. Gérard, C. Jaeger, X. Qing, J. Tisserand, J. Jarazo, K. Hemmer, A. Harms, R. Halder, P. Lucarelli, E. Berger, P. M. A. Antony, E. Glaab, T. Hankemeier, C. Klein, T. Sauter, L. Sinkkonen, J. C. Schwamborn, Impaired serine metabolism complements LRRK2-G2019S pathogenicity in PD patients Parkinsonism, Parkinsonism & Related Disorders (2019), Vol. 67, No. 1, pp. 48 (full-text online) [BibTeX]
  67. D. Grossmann, C. Berenguer-Escuder, M. E. Bellet, D. Scheibner, J. Bohler, F. Massart, D. Rapaport, A. Skupin, A Fouquier d'Hérouël, M. Sharma, J. Ghelfi, A. Rakovic, P. Lichtner, P. Antony, E. Glaab, P. May, K. S. Dimmer, J. C. Fitzgerald, A. Gruenewald, R. Krüger, Mutations in RHOT1 disrupt ER-mitochondria contact sites interfering with calcium homeostasis and mitochondrial dynamics in Parkinson's disease, Antioxidants & Redox Signaling (2019), Vol. 31, No. 16, pp. 1213 (original article) [BibTeX]
  68. C. Berenguer-Escuder, D. Grossmann, F. Massart, P. Antony, L. Burbulla, E. Glaab, S. Imhoff, J. Trinh, P. Seibler, A. Gruenewald, R. Krüger, Variants in Miro1 Cause Alterations of ER-Mitochondria Contact Sites in Fibroblasts from Parkinson's Disease Patients, Journal of Clinical Medicine (2019), Vol. 8, No. 12, 2226 (original article) [BibTeX]
  69. E. Glaab, P. Antony, S. Köglsberger, J. I. Forster, M. L. Cordero-Maldonado, A. Crawford, P. Garcia, M. Buttini, Transcriptome profiling data reveals Ubiquitin-Specific Peptidase 9 knockdown effects, Data in Brief (2019), Vol. 25, 104130 (full-text online) [BibTeX]
  70. A. Kishore, A. Ashok Kumar Sreelatha, M. Sturm, F. von-Zweydorf, L. Pihlstrøm, F. Raimondi, R. Russell, P. Lichtner, M. Banerjee, S. Krishnan, R. Rajan, International Parkinson's Disease Genomics Consortium (IPDGC), COURAGE-PD Consortium, et al., Understanding the role of genetic variability in LRRK2 in Indian population, Movement Disorders (2019), Vol. 34, No. 4, pp. 496 (full-text online) [BibTeX]
  71. C. Blauwendraat, D.A. Kia, L. Pihlstrøm, Z. Gan-Or, S. Lesage, J.R. Gibbs, J. Ding, R.N. Alcalay, S. Hassin-Baer, A.M. Pittman, J. Brooks, International Parkinson's Disease Genomics Consortium (IPDGC), COURAGE-PD Consortium, et al. Insufficient evidence for pathogenicity of SNCA His50Gln (H50Q) in Parkinson's disease, Neurobiology of Aging (2018), Vol. 64, pp. 159 (full-text online) [BibTeX]
  72. C. Blauwendraat, X. Reed, D.A. Kia, Z. Gan-Or, S. Lesage, L. Pihlstrøm, R. Guerreiro, J.R. Gibbs, M. Sabir, S. Ahmed, J. Ding, COURAGE-PD Consortium, French Parkinson’s Disease Consortium, International Parkinson’s Disease Genomics Consortium (IPDGC), et al. Frequency of Loss of Function Variants in LRRK2 in Parkinson Disease, JAMA Neurology (2018), Vol. 75,, 11, pp. 1416 (full-text online) [BibTeX]
  73. E. Glaab, Computational systems biology approaches for Parkinson's disease, Cell and Tissue Research (Special issue "Parkinson's disease: Molecules, cells, and circuitries", T. Gasser, H. Braak, K. Del Tredici, Eds., 2018), Vol. 373, No. 1, pp. 91 (full-text online) [BibTeX]
  74. S. Bolognin, M. Fossepre, X. Qing, J. Jarazo, J. Šcancar, E. Lucumi Moreno, S. L. Nickles, K. Wasner, N. Ouzren, J. Walter, A. Grünewald, E. Glaab, L. Salamanca, R. M. T. Fleming, P. Antony, J. C. Schwamborn, 3D cultures of Parkinson's disease specific dopaminergic neurons for high content phenotyping and drug testing, Advanced Science (2018), Vol. 6, No. 1, 1800927 (full-text online) [BibTeX]
  75. D. Hartl, P. May, W. Gu, M. Mayhaus, S. Pichler, C. Spaniol, E. Glaab, D. Bobbili, P. Antony, S. Koeglsberger, A. Kurz, T. Grimmer, K. Morgan, B. Vardarajan, C. Reitz, J. Hardy, J. Bras, R. Guerreiro, R. Balling, J. Schneider, M. Riemenschneider, A rare loss-of function variant of ADAM17 is associated with late-onset familial Alzheimer disease, Molecular Psychiatry (2018), Vol. 25, No. 3, pp. 629 (full-text online) [BibTeX]
  76. J. Nyffeler, P. Chovancova, X. Dolde, A. Holzer, V. Purvanov, I. Kindinger, A. Kerins, D. Higton, S. Silvester, B. M. A. van Vugt-Lussenburg, E. Glaab, B. van der Burg, R. Maclennan, D. F. Legler, M. Leist, A structure-activity relationship linking non-planar PCBs to functional deficits of neural crest cells: new roles for connexins, Archives of Toxicology (2018), Vol. 92, No. 3, pp. 1225–1247 (doi: 10.1007/s00204-017-2125-4, full-text online) [BibTeX]
  77. C. Blauwendraat, F.Faghri, L. Pihlstrøm, J.T. Geiger, A. Elbaz, S. Lesage, J.C. Corvol, P. May, A. Nicolas, Y. Abramzon, N.A. Murphy, International Parkinson's Disease Genomics Consortium (IPDGC), COURAGE-PD Consortium, et al. NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases, Neurobiology of Aging (2017), Vol. 57, pp. 247 full-text online) [BibTeX]
  78. J. Fitzgerald, A. Zimprich, D. A. Carvajal-Berrio, K. M. Schindler, B. Maurer, C. Schulte, A. Hauser, M. Kübler, R. Lewin, D. R. Bobbili, L. M. Schwarz, E. Vartholomaiou, K. Brockmann, R. Wüst, J. Madlung, A. Nordheim, O. Riess, L. M. Martins, E. Glaab, P. May, K. Schenke-Layland, D. Picard, M. Sharma, T. Gasser, R. Krüger, Metformin reverses TRAP1 mutation-associated alterations in mitochondrial function in Parkinson's disease, Brain (2017), Vol. 140, No. 9, pp. 2444 (full-text online) [BibTeX]
  79. E. Glaab, Using prior knowledge from cellular pathways and molecular networks for diagnostic specimen classification, Briefings in Bioinformatics (2016), Vol. 17, No. 3, pp. 440 (full-text online) [BibTeX]
  80. A. Ashrafi, P. Garcia, H. Kollmus, K. Schughart, A. del Sol, M. Buttini, E. Glaab, 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 (2017), Vol. 58, pp. 30 (full-text online) [BibTeX]
  81. S. Köglsberger, M. L. Cordero-Maldonado, P. Antony, J. I. Forster, P. Garcia, M. Buttini, A. Crawford, E. Glaab, Gender-specific expression of ubiquitin-specific peptidase 9 modulates tau expression and phosphorylation: possible implications for tauopathies, Molecular Neurobiology (2017), Vol 54, No. 10, pp. 7979 (full-text online) [BibTeX]
  82. C. Singh, E. Glaab, C. Linster, Molecular Identification of D-Ribulokinase in Budding Yeast and Mammals, Journal of Biological Chemistry (2017), Vol 292, No. 3, pp. 1005 (full-text online) [BibTeX]
  83. S. Kleiderman, S. Gutbier, K. U. Tufekci, F. Ortega, J. V. Sá, A. P. Teixeira, C. Brito, E. Glaab, B. Berninger, P. M. Alves, M. Leist, Conversion of non-proliferating astrocytes into neurogenic neural stem cells: control by FGF2 and IFN-gamma, Stem Cells (2016), Vol. 34, No. 12, pp. 2861 (full-text online) [BibTeX]
  84. P. Shah, J. Fritz, E. Glaab, M. Desai, K. Greenhalgh, A. Frachet, M. Niegowska, M. Estes, C. Jäger, F. Zenhausen, P. Wilmes, A microfluidics-based in vitro model of the gastrointestinal human-microbe interface, Nature Communications (2016), Vol. 7, No. 11535 (full-text online) [BibTeX]
  85. G. I. Allen, N. Amoroso, C. Anghel, V. Balagurusamy, C. J. Bare, D. Beaton, R. Bellotti, D. A. Bennett, K. Boehme, P. C. Boutros, L. Caberlotto, C. Caloian, F. Campbell, E. C. Neto, Y. Chang, B. Chen, C. Chen, T. Chien, T. Clark, S. Das, C. Davatzikos, J. Deng, D. Dillenberger, R. J. B. Dobson, Q. Dong, J. Doshi, D. Duma, R. Errico, G. Erus, E. Everett, D. W. Fardo, S. H. Friend, H. Fröhlich, J. Gan, P. St. George-Hyslop, S. S. Ghosh, E. Glaab, R. C. Green, Y. Guan, M. Hong, C. Huang, J. Hwang, J. Ibrahim, P. Inglese, Q. Jiang, Y. Katsumata, J. S. K. Kauwe, A. Klein, D. Kong, R. Krause, E. Lalonde, M. Lauria, E. Lee, X. Lin, Z. Liu, J. Livingstone, B. A. Logsdon, S. Lovestone, A. Lyappan, M. Ma, A. Malhotra, L. M. Mangravite, T. J. Maxwel, E. Merrill, J. Nagorski, A. Namasivayam, M. Narayan, M. Naz, S. J. Newhouse, T. C. Norman, R. N. Nurtdinov, Y. Oyang, Y. Pawitan, S. Peng, M. A. Peters, S. R. Piccolo, P. Praveen, C. Priami, V. Y. Sabelnykova, P. Senger, X. Shen, A. Simmons, A. Sotiras, G. Stolovitzky, S. Tangaro, A. Tateo, Y. Tung, N. J. Tustison, E. Varol, G. Vradenburg, M. W. Weiner, G. Xiao, L. Xie, Y. Xie, J. Xu, H. Yang, X. Zhan, Y. Zhou, F. Zhu, H. Zhu, S. Zhu, Alzheimer's Disease Neuroimaging Initiative, Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease, Alzheimer's and Dementia (2016), Vol. 12, No. 6, pp. 645 (full-text online) [BibTeX]
  86. C. Jaeger*, E. Glaab*, A. Michelucci*, T. M. Binz, S. Koeglsberger, P. Garcia, J. P. Trezzi, J. Ghelfi, R. Balling, M. Buttini, The Mouse Brain Metabolome: Region-Specific Signatures and Response to Excitotoxic Neuronal Injury, American Journal of Pathology (2015), Vol. 185, No. 6, pp. 1699 (*these authors contributed equally to this work, online first) [BibTeX]
  87. S. Kleiderman, J. Sá, A. Teixeira, C. Brito, S. Gutbier, L. Evje, M. Hadera, E. Glaab, M. Henry, S. Agapios, P. Alves, U. Sonnewald, M. Leist, Functional and phenotypic differences of pure populations of stem cell-derived astrocytes and neuronal precursor cells, Glia (2016), Vol. 64, No. 5, pp. 695 (full-text online) [BibTeX]
  88. E. Glaab, Building a virtual ligand screening pipeline using free software: a survey, Briefings in Bioinformatics (2016), Vol. 17, No. 2, pp. 352(full-text online) [BibTeX]
  89. N. Casadei, P. Sood, T. Ulrich, N. Kieper, S. Helling, C. May, E. Glaab, J. Chen, K. Marcus, D. Rapaport, T. Ott, O. Riess, R. Krueger, J. Fitzgerald, Mitochondrial Defects and Neurodegeneration in Mice Overexpressing Wild Type or G399S Mutant HtrA2, Human Molecular Genetics (2016), Vol. 25, No. 3, pp. 459 (full-text online) [BibTeX]
  90. E. Glaab, R. Schneider, RepExplore: Addressing technical replicate variance in proteomics and metabolomics data analysis, Bioinformatics (2015), Vol. 31, No. 13, pp. 2235 (full-text online) [BibTeX]
  91. N. Vlassis, E. Glaab, GenePEN: analysis of network activity alterations in complex diseases via the pairwise elastic net, Statistical Applications in Genetics and Molecular Biology (2015), Vol. 14, No. 2, pp. 221 (full-text online) [BibTeX]
  92. L. Grandbarbe, S. Gabel, E. Koncina, G. Dorban, T. Heurtaux, C. Birck, E. Glaab, A. Michelucci, P. Heuschling, Inflammation promotes a conversion of astrocytes into neural progenitor cells via NF-kB activation, Molecular Neurobiology (2016), Vol. 53, No. 8, pp. 5041 (full-text online) [BibTeX]
  93. E. Glaab, R. Schneider, Comparative pathway and network analysis of brain transcriptome changes during adult aging and in Parkinson's disease, Neurobiology of Disease (2015), Vol. 74, pp. 1 (full-text online) [BibTeX]
  94. C. Birck, E. Koncina, T. Heurtaux, E. Glaab, A. Michelucci, P. Heuschling, L. Grandbarbe, Transcriptomic analyses of primary astrocytes under TNF-alpha treatment, Genomics Data (2015), Vol. 7, pp. 7 (full-text online) [BibTeX]
  95. M. Maes, G. Nowak, J. R Caso, J. C. Leza, C. Song, M. Kubera, H. Klein, P. Galecki, C. Noto, E. Glaab, R. Balling, M. Berk, Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research, Molecular Neurobiology (2016), Vol. 53, No. 5, pp. 2927 (full-text online) [BibTeX]
  96. K. Righetti, J. L. Vu, S. Pelletier, B. L. Vu, E. Glaab, D. Lalanne, A. Pasha, R. V. Patel, N. Provart, J. Verdier, O. Leprince, 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, The Plant Cell (2015), Vol. 27, No. 10, pp. 2692-2708 (full-text online) [BibTeX]
  97. K. A. Fujita, M. Ostaszewski, Y. Matsuoka, S. Ghosh, E. Glaab, C. Trefois, I. Crespo, T. M. Perumal, W. Jurkowski, P. M. A. Antony, N. Diederich, M. Buttini, A. Kodama, V. P. Satagopam, S. Eifes, A. del Sol, R. Schneider, H. Kitano, R. Balling Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map, Molecular Neurobiology (2014), Vol. 49, No. 1, pp. 88 (full-text online) [BibTeX]
  98. S. Ballereau, E. Glaab, A. Kolodkin, A. Chaiboonchoe, M. Biryukov, N. Vlassis, H. Ahmed, J. Pellet, N. Baliga, L. Hood, R. Schneider, R. Balling, C. Auffray, Functional genomics and bioinformatics for systems biology, Springer book in Systems Biology, Vol. 1: Systems Biology: Integrative Biology and Simulation Tools (2013), Spinger [BibTeX]
  99. A. Chaiboonchoe, W. Jurkowski, J. Pellet, E. Glaab, A. Kolodkin, A. Raussel, A. Le Béchec, L. Meyniel, S. Ballereau, I. Crespo, H. Ahmed, V. Volpert, V. Lotteau, N. Baliga, L. Hood, A. del Sol; R. Balling, C. Auffray, Network analysis for systems biology, Springer book in Systems Biology, Vol. 1: Systems Biology: Integrative Biology and Simulation Tools (2013), Spinger [BibTeX]
  100. E. Muller, E. Glaab, P. May, N. Vlassis, P. Wilmes, Condensing the omics fog of microbial communities, Trends in Microbiology (2013), Vol. 21, No. 7, pp. 325 (full-text online) [BibTeX]
  101. E. Glaab, A. Baudot, N. Krasnogor, R. Schneider, A. Valencia, EnrichNet: network-based gene set enrichment analysis, Bioinformatics (Proceedings of the European Conference on Computational Biology, ECCB 2012), Vol. 28, No. 18, pp. i451 (acceptance rate: 14%, full-text online) [BibTeX]
  102. E. Glaab, R. Schneider, PathVar: analysis of gene and protein expression variance in cellular pathways using microarray data, Bioinformatics (2012), Vol. 28, No. 3, pp. 446 (see full text online) [BibTeX]
  103. E. Glaab, J. Bacardit, J. M. Garibaldi, N. Krasnogor, Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data, PLoS ONE (2012), Vol. 7, No. 7, e39932 (see online full text) [BibTeX]
  104. E. Glaab, Analysing functional genomics data using novel ensemble, consensus and data fusion techniques, PhD thesis, School of Computer Science, University of Nottingham, 2011 [BibTeX]
  105. G. W. Bassel, E. Glaab, J. Marquez, M. J. Holdsworth, J. Bacardit, Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets, Plant Cell (2011), Vol. 23, No. 9, pp. 3101 (see online full text) [BibTeX]
  106. G. W. Bassel, H. Lan, E. Glaab, D. J. Gibbs, T. Gerjets, N. Krasnogor, A. J. Bonner, M. J. Holdsworth, N. J. Provart, A genome-wide network model capturing seed germination reveals co-ordinated regulation of plant cellular phase transitions, Proc. Natl. Acad. Sci. USA (2011), Vol. 108, No. 23, pp. 9709 (see online full text, the SeedNet webpage and articles on Science Daily and Futurity) [BibTeX]
  107. D. S. Gardner, P. Rhodes, A. Karamitri, E. Glaab, S. M. Rhind, A low protein diet during early gestation in sheep detrimentally impacts hepatic glucose metabolism in the adult offspring, Proceedings of the Nutrition Society 2011, Vol. 70, E196 full-text online [BibTeX]
  108. E. Glaab, A. Baudot, N. Krasnogor, A. Valencia, Extending pathways and processes using molecular interaction networks to analyse cancer genome data, BMC Bioinformatics (RECOMB Computational Cancer Biology 2010, Oslo, Norway), Vol. 11, No. 1, 597 (received designation: highly accessed, full-text online) [BibTeX]
  109. E. Glaab, A. Baudot, N. Krasnogor, A. Valencia, TopoGSA: network topological gene set analysis, Bioinformatics (2010), Vol. 26, No. 9, pp. 1271. full-text online [BibTeX]
  110. E. Glaab, J. M. Garibaldi, N. Krasnogor, ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization, BMC Bioinformatics (2009), Vol. 10, No. 1., 358. full-text online [BibTeX]
  111. E. Glaab, J. M. Garibaldi, N. Krasnogor, Learning pathway-based decision rules to classify microarray cancer samples, German Conference on Bioinformatics 2010, Lecture Notes in Informatics (LNI), Vol. 173, 123-134. full-text online [BibTeX]
  112. E. Glaab, J. M. Garibaldi and N. Krasnogor, VRMLGen: An R package for 3D Data Visualization on the Web, Journal of Statistical Software (2010), Vol. 36, No. 8, 1-18 full-text online [BibTeX]
  113. H. O. Habashy, D. G. Powe, E. Glaab, N. Krasnogor, J. M. Garibaldi, E. A. Rakha, G. Ball, A. R Green, C. Caldas, I. O. Ellis, RERG (Ras-related and oestrogen-regulated growth-inhibitor) expression in breast cancer: A marker of ER-positive luminal-like subtype, Breast Cancer Research and Treatment (2011), Vol. 128, No. 2, 315-326 full-text online [BibTeX]
  114. E. Glaab, Methods for Comparative Molecular Field Analysis in the Biochemical Algorithms Library (BALL), Master thesis, Saarland University, 2007 [BibTeX]
  115. E. Glaab, On the predictability of CpG methylation in human tissue at single basepair resolution, Bachelor thesis, Saarland University, 2006 [BibTeX]


Enrico Glaab