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HTML and CSS template for the Howto Cards (preview at https://lcsb.pages.uni.lu/howto/template )

Training materials for the MINERVA Platform

Additional Supporting Information to "Occurrence and Distribution of Pharmaceuticals and their Transformation Products in Luxembourgish Surface Waters" by Singh et al.

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.

https://howto.lcsb.uni.lu

EHR-Challenge-distro

Method testing and analyses of Oxford Nanopore Technology (ONT) sequencing runs Data obtained by sequencing "generous donor B" across several runs Original data prepared by Rashi (post-sequencing) Initial analyses performed by CCL

Software development guidelines for handling sensitive data in HPC (à la carte approach)

A package and environment with the NestedCV() class - a scikit-learn compatible class for nested cross-validation.

https://howto.lcsb.uni.lu

MiBiPa 2-HP project

Mouse microglia regional heterogeneity in single cell resolution