Elisa Gómez de Lope
A5048997519- Parkinson's Disease Mechanisms and Treatments
- Gene expression and cancer classification
- Biochemical and Molecular Research
- Bioinformatics and Genomic Networks
- Folate and B Vitamins Research
- Advanced Causal Inference Techniques
- Autophagy in Disease and Therapy
- Cell Image Analysis Techniques
- Machine Learning and Data Classification
University of Luxembourg
2022-2024
Luxembourg Institute of Health
2024
Abstract Parkinson’s disease (PD) is a highly heterogeneous disorder influenced by several environmental and genetic factors. Effective disease-modifying therapies robust early-stage biomarkers are still lacking, an improved understanding of the molecular changes in PD could help to reveal new diagnostic markers pharmaceutical targets. Here, we report results from cohort-wide blood plasma metabolic profiling patients controls Luxembourg Study detect disease-associated alterations at level...
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Abstract Introduction While there is an interest in defining longitudinal change people with chronic illness like Parkinson’s disease (PD), statistical analysis of data not straightforward for clinical researchers. Here, we aim to demonstrate how the choice method may influence research outcomes, (e.g., progression apathy), specifically size effect estimates, a cohort. Methods In this retrospective 802 typical Luxembourg Parkinson's study, compared mean apathy scores at visit 1 and 8 by...
Omics data analysis is crucial for studying complex diseases, but its high dimensionality and heterogeneity challenge classical statistical machine learning methods. Graph neural networks have emerged as promising alternatives, yet the optimal strategies their design optimization in real-world biomedical challenges remain unclear. This study evaluates various graph representation models case-control classification using high-throughput biological from Parkinson's disease control samples. We...