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An exploration on gene expression data was carried out on single-cell RNAseq analyses of bronchoalveolar lavages from nine COVID-19 patients, three moderate cases, severe case and critical cases, comparing with healthy subjects.
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Environmental Cheminformatics / PubChem Docs
Artistic License 2.0A home for documentation, scripts etc related to PubChem efforts
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Elisa Gomezdelope / GRL_sample_similarity_PD
MIT LicenseGraph representation learning modelling pipeline exploiting sample-similarity networks derived from high-throughput omics profiles to learn PD-specific fingerprints from the spatial distribution of molecular abundance similarities in an end-to-end fashion. The scripts apply the graph representation learning modelling pipeline on sample-similarity networks of transcriptomics and metabolomics data from the PPMI and the LuxPARK cohort, respectively.
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Miroslav Kratochvil / minervaR
GNU General Public License v3.0 onlyR code for an interface to MINERVA API and helper functions
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IMP / IMP3
MIT LicenseUpdated -
This GitLab folder provides the scripts that were used in my Master Thesis Project. For any types of questions, please feel free to contact me.
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Environmental Cheminformatics / PD cheminformatics pipeline
Artistic License 2.0Updated -
Computational modelling and simulation / GeneRegulationAnalysis
GNU Affero General Public License v3.0Gene regulation inference of COVID-19
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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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TNG / papers / PD GBM Publication
Apache License 2.0Updated -
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BDS / Ml Dyskinesia
MIT LicenseUpdated -
Jacek Lebioda / ChemPert
GNU Affero General Public License v3.0Updated -