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PubChem PFAS

Repository for all slides related to R3 courses.

Code related to Talavera Andujar et al DOI: 10.26434/chemrxiv-2023-6j2gm

R package for Gene Regulatory Networks

Graph representation learning modelling pipeline exploiting molecular interaction networks of transcriptomics (protein-protein interactions) and metabolomics (metabolite-metabolite interactions) to learn PD-specific fingerprints from the spatial distribution of molecular relationships in an end-to-end fashion. The scripts apply the graph representation learning modelling pipeline on networks of molecular interactions, where transcriptomics and metabolomics data from the PPMI and the LuxPARK cohort, respectively, are projected.

Pre-screening mass spectrometry data.

This repository contains the code for ML analyses performed in Chapter 5 of my PhD thesis "Interpretable machine learning on omics data for the study of UPDRS III prognosis". The project consists on predicting the Unified Parkinson’s Disease Rating Scale Part III (UPDRS III) motor scores (mild/severe when classification) from whole blood transcriptomics and blood plasma metabolomics using measurements from the baseline clinical visit, and temporal or dynamic features engineered from a short temporal series of 4 and 3 timepoints, respectively, from the PPMI cohort and the LuxPARK cohort, aiming at identifying molecular and higher-level functional fingerprints linked specifically to the motor symptoms in PD.

Playground for experiments on the official http://bioconductor.org/packages/devel/bioc/html/RMassBank.html

Repository for all slides related to R3 courses.