Explore projects
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Code used for the analysis of the RNA-seq, ATAC-seq and ChIP-seq datasets produced in this study. Original fastq files deposited in https://ega-archive.org/, under the accession number EGAD00001009288.
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Laura Denies / PathoFact
GNU General Public License v3.0 or laterUpdated -
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Repository for NORMAN-SLE work organization at ECI, including list tracking, updates and documentation. Main representatives: Emma and Hiba.
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Malte Herold / LAOTS_niche_ecology_analysis
GNU General Public License v3.0 onlyRepository for scripts used in the analyses for the publication "Integration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance"
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Environmental Cheminformatics / ShinyTPs
Artistic License 2.0ShinyTPs: Curate transformation products from text mining results from HSDB & PubChem
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This repository contains the code for statistical analyses performed in Chapter 3 of my thesis "Cross-sectional and longitudinal profiling of PD transcriptomics and metabolomics". The project consists on whole blood transcriptomics and blood plasma metabolomics cross-sectional and longitudinal profiling of Parkinson's disease patients and controls from the PPMI cohort and the LuxPARK cohort respectively, to identify differential molecular and higher-level functional features in PD.
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Matthieu Gobin / r3-pages
Creative Commons Zero v1.0 UniversalRepository for building the official website of the R3 lab.
Here is the presence on the university website.
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CBG / RNetDys
GNU General Public License v2.0 or laterThis is a mirror from https://github.com/BarlierC/RNetDys.
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Francesco Nasta / basic-practice-pages
MIT LicenseBasic practice repository for git trainings
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Elisa Gomezdelope / ML_PD_metab_transc
MIT LicenseThis repository contains the code for ML analyses performed in Chapter 4 of my PhD thesis "Interpretable Machine Learning on omics data for biomarker discovery in Parkinson's disease". The project consists on performing Parkinson's disease (PD) case-control classification from blood plasma metabolomics measurements at the baseline clinical visit from the LuxPARK cohort, and from whole blood transcriptomics data at baseline as well as dynamic features engineered from a short temporal series of 4 timepoints from the PPMI cohort. The study involves evaluation of different feature selection strategies, The goal was to build and test a collection of ML models and, most interestingly, identify molecular and higher-level functional representations associated with PD diagnosis.
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ICS-lcsb / NET-Ca-mito
Apache License 2.0Updated -
Elisa Gomezdelope / basic-practice-pages
MIT LicenseBasic practice repository for git trainings
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ESB / ONT_pilot_gitlab
GNU General Public License v3.0 or laterMethod 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 CCLUpdated