Explore projects
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COVID-19 / models
GNU General Public License v3.0 onlyComputational models of different aspects of COVID-19
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elixir / beacon
Apache License 2.0ELIXIR Luxembourg's GA4GH Beacon API implementation in Python
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SMASCH / scheduling-system
GNU Affero General Public License v3.0Scheduling assignments for Parkinson Research Clinic
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genomeanalysis / LuxPARK
Apache License 2.0Updated -
Environmental Cheminformatics / pubchem
Artistic License 2.0A project for interactions with PubChem
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IMP / IMP3
MIT LicenseUpdated -
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R3 / outreach / templates / presentations / markdown
Creative Commons Zero v1.0 UniversalUpdated -
ESB / CO-INFECTOMICS
MIT LicenseCO-INFECTOMICS - identification of co-infections and other factors associated with COVID-19 severity in the gut microbiome
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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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Francesco Nasta / basic-practice-pages
MIT LicenseBasic practice repository for git trainings
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This project hosts the JSON schemas used for representing the metadata of submissions to the ELIXIR translational data repository. It also provides validation utility methods.
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R3 / outreach / papers / cobrexa / benchmarks
Apache License 2.0Benchmark scripts related to the COBREXA.jl publication
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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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