An unsupervised transfer learning approach for rare disease transcriptomics
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Updated
Jan 27, 2020 - HTML
An unsupervised transfer learning approach for rare disease transcriptomics
A Tidy Framework to Hack Gene Expression Signatures
Brain Cell Type Specific Gene Expression Analysis
Unbiased single-cell transcriptomic data cell type identification
Non-Negative Matrix Factorization for Gene Expression Clustering
The web application for the crowdsourced gene expression signatures: http://amp.pharm.mssm.edu/creeds/
Shared TREM-1 expression signatures of asthma affection and control
Web application that enables users to compare the expression of genes or enrichment of gene sets between different molecular subtypes of colorectal cancer
NanostrIng MB cLassifiEr
Development and validation of a robust RNA-seq based prognostic signature in non-small cell lung cancer
Code repository for SFARI Genes and where to find them; classification modelling to identify genes associated with Autism Spectrum Disorder from RNA-seq data
A library and toolkit for common representation and analysis of gene expression profile data
A repository that contains all the code for the interactive Shiny app of the models developed in our work on predicting response to neoadjuvant treatment.
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