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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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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 -
Elisa Gomezdelope / basic-practice-pages
MIT LicenseBasic practice repository for git trainings
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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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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.
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Deployment and CI scriptage for the static sites
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Elisa Gomezdelope / ML_UPDRSIII_metab_transc
MIT LicenseThis 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.
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Annegrät Daujeumont / howto-cards
Creative Commons Zero v1.0 UniversalUpdated -
Nils Christian / minerva
GNU Affero General Public License v3.0MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format.
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Soumyabrata Ghosh / jkan
MIT LicenseA lightweight, backend-free open data portal, powered by Jekyll
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Marina Popleteeva / courses
Creative Commons Zero v1.0 UniversalRepository for all slides related to R3 courses.
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core-services / haddoc
MIT LicenseLCSB flavoured Jekyll theme for documentation and complex static site
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DVB / Monzel_2020
Apache License 2.0Updated -
Fasavanh Sanichanh / howto-cards
Creative Commons Zero v1.0 UniversalUpdated