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GOMEZ DE LOPE Elisa

University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)

ORCID
0000-0002-7115-7393
Main Referenced Co-authors
GLAAB, Enrico  (5)
Diaz-Uriarte, R. (1)
Fröhlich, H. (1)
Giugno, R. (1)
Liò, Pietro (1)
Main Referenced Keywords
machine learning (5); Parkinson's disease (3); pathways (3); networks (2); omics (2);
Main Referenced Unit & Research Centers
Luxembourg Centre for Systems Biomedicine (LCSB): Biomedical Data Science (Glaab Group) (3)
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (7)
Biochemistry, biophysics & molecular biology (5)
Life sciences: Multidisciplinary, general & others (4)
Computer science (2)
Human health sciences: Multidisciplinary, general & others (2)

Publications (total 8)

The most downloaded
93 downloads
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. https://hdl.handle.net/10993/56048

The most cited

10 citations (Scopus®)

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 https://hdl.handle.net/10993/51787

GOMEZ DE LOPE, E. (2024). Interpreting Omics Data in Parkinson’s Disease: A Statistical, Machine Learning, and Graph Representation Learning Approach [Doctoral thesis, Unilu - Université du Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/60638

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.

GOMEZ DE LOPE, E. (13 July 2023). LuxPARK Metabolomics data analysis and modelling [Paper presentation]. Luxembourg Center for Systems Biomedicine department meeting.

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

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.

GOMEZ DE LOPE, E. (18 November 2022). Machine learning for the study of Parkinson’s Disease diagnosis and associated mechanisms [Paper presentation]. PhD days, University of Luxembourg.

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

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

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