Publications

Filali, A., Jeancolas, L., Mangone, G., Sambin, S., Chalançon, A., Gomes, M., ... & Petrovska-Delacrétaz, D. (2023):
"Early-stage parkinson's disease detection based on action unit derivatives“ In 9ème Colloque en TéléSANté et dispositifs biomédicaux:" Dispositifs biomédicaux et technologies numériques en santé; des besoins aux usages" (Colloque JETSAN).
https://hal.science/hal-04178781


Birkenbihl, C., Ahmad, A., Massat, N. J., Raschka, T., Avbersek, A., Downey, P., ... & Fröhlich, H. (2023):
"Artificial intelligence-based clustering and characterization of Parkinson's disease trajectories." Scientific Reports, 13(1), 2897.
https://www.nature.com/articles/s41598-023-30038-8


Sood, M., Suenkel, U., von Thaler, A. K., Zacharias, H. U., Brockmann, K., Eschweiler, G. W., ... & Heinzel, S. (2023):
"Bayesian network modeling of risk and prodromal markers of Parkinson’s disease." Plos one, 18(2), e0280609.
https://doi.org/10.1371/journal.pone.0280609


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(1), 1-16.
https://www.nature.com/articles/s41531-023-00446-8


Pavelka, L., Rauschenberger, A., Landoulsi, Z., Pachchek, S., Marques, T., Gomes, C. P., ... & Krüger, R. (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, (Preprint), 1-13.
https://content.iospress.com/articles/journal-of-parkinsons-disease/jpd223511


Diaz-Uriarte, R., Gómez de Lope, E., Giugno, R., Fröhlich, H., Nazarov, P. V., Nepomuceno-Chamorro, I. A., ... & Glaab, E. (2022):
"Ten quick tips for biomarker discovery and validation analyses using machine learning. PLoS computational biology"
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010357


Aborageh, M., Krawitz, P., & Fröhlich, H. (2022):
"Genetics in parkinson’s disease: From better disease understanding to machine learning based precision medicine." Frontiers in Molecular Medicine, 11.

https://internal-journal.frontiersin.org/articles/10.3389/fmmed.2022.933383/full


Pauly, C., Glaab, E., Hansen, M., Martin-Gallausiaux, C., Ledda, M., Marques, T., ... & Krüger, R. (2022):
"Parkinson's Disease progression, resilience and inflammation markers during the COVID-19 pandemic."
Movement Disorders, (in press), in-press.
https://orbilu.uni.lu/handle/10993/51932


Pavelka, L., Rauschenberger, A., Landoulsi, Z., Pachchek, S., May, P., Glaab, E., & Krüger, R. (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, 8(1), 1-10.
https://www.nature.com/articles/s41531-022-00342-7


Holger Fröhlich, Noemi Bontridder, Dijana Petrovska-Delacrétaz, Enrico Glaab, Felix Kluge, Mounîm A. EL Yacoubi, Mayca Marin Valero, Jean-Christophe Corvol, Bjoern M Eskofier, Jean Marc, Stephane Lehericy, Jürgen Winkler and Jochen Klucken (2022):
"Leveraging the Potential of Digital Technology for Better Individualized Treatment in Parkinson’s Disease Frontiers of Neurology 2022"
https://doi.org/10.3389/fneur.2022.788427


Laetitia Jeancolasa, Graziella Mangonec, Dijana Petrovska-Delacrétazb, Habib Benalie, Badr-Eddine Benkelfatb, Isabelle Arnulfc, Jean-Christophe Corvol, Marie Vidailhetc, Stéphane Lehéricy (2022):
"Voice characteristics from isolated rapid eye movement sleep behaviordisorder to early Parkinson's disease Parkinsonism and Related Disorders 2022" https://www.sciencedirect.com/science/article/pii/S1353802022000037


Biondetti E, Santin MD, Valabrègue R, Mangone G, Gaurav R, Pyatigorskaya N, Hutchison M, Yahia-Cherif L, Villain N, Habert MO, Arnulf I, Leu-Semenescu S, Dodet P, Vila M, Corvol JC, Vidailhet M, Lehéricy S (2021):
"The spatiotemporal changes in dopamine, neuromelanin and iron characterizing Parkinson's disease", Brain. 2021 May 12:awab191. doi: 10.1093/brain/awab191. Online ahead of print.


Armin Rauschenberger, Enrico Glaab (2021):
"Predicting correlated outcomes from molecular data Bioinformatics 2021"
https://academic.oup.com/bioinformatics/article/37/21/3889/6343445


Jeancolas L, Petrovska-Delacretaz D, Mangane G, Benkelfat BE, Corvol JC, Vidailhet M, Lehericy S, Benali H. (2021): 
"X-Vectors: new quantitative biomarkers for early Parkinson's disease detection from speech". Frontiers in Neuroinformatics 2021 Feb 19;15:578369. 
https://doi.org/10.3389/fninf.2021.578369


S.K. 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, N. Rad, E. Rainaldi, S. Sapienza, P. Schwab, N. Shokhirev, M. Venäläinen, G. Vergara-Diaz, Y. Zhang,  the Parkinson's Disease Digital Biomarker DREAM Challenge Consortium,  Y. Wang, Y. Guan, D. Brunner, P. Bonato, L. Mangravite, L. Omberg (2021): 
"Crowdsourcing digital health measures to predict Parkinson's disease severity:  the Parkinson's Disease Digital Biomarker DREAM Challenge", npj Digital Medicine, volume 4, Article number: 53 (2021)


Gassner H, Sanders P, Dietrich A, Marxreiter F, Eskofier BM, Winkler J, Klucken J (2020):
"Clinical Relevance of Standardized Mobile Gait Tests. Reliability Analysis Between Gait Recordings at Hospital and Home in Parkinson's Disease: A Pilot Study“. J Parkinsons Dis 10:1763-1773, 10.3233/JPD-202129 (IF 5.178) 


Mohammad Asif Emon, Ashley Heinson, Ping Wu, Daniel Domingo-Fernandez, Meemansa Sood, Henri Vrooman, Jean-Christophe Corvol, Phil Scordis, Martin Hofmann-Apitius, Holger Fröhlich (2020):
"Clustering of Alzheimer's and Parkinson's Disease Based on Genetic Burden of Shared Molecular Mechanisms", Scientific Reports, 10, Article number: 19097.


Luise Gootjes-Dreesbach, Meemansa Sood, Akrishta Sahay, Martin Hofmann-Apitius, Holger Fröhlich (2020): 
"Variational Autoencoder Modular Bayesian Networks (VAMBN) for Simulation of Heterogeneous Clinical Study Data", Frontiers in Big Data: Medicine and Public Heafth, doi: 10.3389/fdata.2020.00016.


Johann de Jong, Mohammad Asif Emon, Ping Wu, Reagan Karki, Meemansa Sood, Patrice Godard, Ashar Ahmad, Henri Vrooman, Martin Hofmann-Apitius, Holger Fröhlich (2019):
"Deep learning for clustering of multivanate clinical patient trajectories with missing values", Giga Science, Volume 8, lssue 11.


E. Glaab, J.P. Trezzi, A. Greuel, C. J ger, Z. Hodak, A. Drzezga, L. Timmermann, M. Tittgemeyer, N. J. Diederich, C. Eggers (2019): 
"Integrative analysis of blood metabolomics and PET brain neuroimaging data for Parkinson's disease", Neurobiology of Oisease (2019), Val. 124, No. 1, pp. 555 (htlps'//doi org/10 1016/j nbd 2019 01 003).


Gallea C, Ewenczyk C, Degos B, Welter ML, Grabli D, Leu-Semenescu S, Valabregue R, Berroir P, Yahia-Cherif L, Bertasi E, Fernandez-Vidal S, Bardinet E, Roze E, Benali H, Poupon C, François C, Arnulf I, Lehéricy S, Vidailhet M (2017):
"Pedunculopontine network dysfunction in Parkinson's disease with postural control and sleep disorders", Mov Disord. 2017 May;32(5):693-704.


Schlachetzki JCM, Barth J, Marxreiter F, Gossler J, Kohl Z, Reinfelder S, Gassner H, Aminian K, Eskofier BM, Winkler J, Klucken J (2017):
"Wearable sensors objectively measure gait parameters in Parkinson's disease“. PLoS One 12:e0183989, 10.1371/journal.pone.0183989 (IF 2.740)


Klucken J, Barth J, Kugler P, Schlachetzki J, Henze T, Marxreiter F, Kohl Z, Steidl R, Hornegger J, Eskofier B, Winkler J (2013):
"Unbiased and mobile gait analysis detects motor impairment in Parkinson's disease“
. PLoS One 8:e56956, 10.1371/journal.pone.0056956 (IF 2.740)


A. Greuel, J. P. Trezzi, E. Glaab, M. C. Ruppert, F Maier, C. J ger, Z. Hodak, L. Timmermann, K. Hiller, M. Tittgemeyer, A. Drzezga, N. Diederich, C. Eggers (2010): 
"GBA variants in Parkinson's disease: clinical, metabolomic and multimodal neuroimaging phenotypes", Movement Disorders (2010), Vol. 35, No. 12, 2201-2210 (http'l/dxdoi org/10 1002/mds 2822S).