The release incorporates an end-to-end training and evaluating of a variational autoencoder applied to model TCGA pan-cancer gene expression data. Future releases will stabilize the pipeline and also introduce novel modeling features and evaluation techniques. Minor Updates: 0.1.1 - Fix legibility of parameter sweep figure
This is the first version of MEGENA co-expression networks and prognostic modules for TCGA pan-cance...
BioBombe analysis applied to gene expression data from The Cancer Genome Atlas (TCGA) PanCanAtlas. ...
Personalized treatment methods for a complex disease such as cancer benefit from using multiple data...
The release incorporates an end-to-end training and evaluating of a variational autoencoder applied ...
Code base to build Pan Cancer classifiers for any combination of genes or cancer types. This release...
Variational Auto-Encoders are a class of machine learning models that have been used in varying cont...
Information about the dataset files: 1) pancan_rnaseq_freeze.tsv.gz: Publicly available gene expres...
The release tracks recent developments in evaluating tybalt models. The release includes an evaluati...
Cancer has been known as a deadly and complex disease to tackle. By applying machine learning algori...
This dataset includes the harmonised version of all The Cancer Genome Atlas (TCGA) RNA-Seq data (33 ...
Publicly available gene expression dataset from TCGA PanCanAtlas.<div><br></div><div>These data are ...
Abstract: The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the N...
The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) offers interactive visualization a...
This is a beta release of workflows for enabling precision medicine to perform neoantigen prediction...
Software to reproduce the analysis for our paper: Predicting drug polypharmacology from cell morphol...
This is the first version of MEGENA co-expression networks and prognostic modules for TCGA pan-cance...
BioBombe analysis applied to gene expression data from The Cancer Genome Atlas (TCGA) PanCanAtlas. ...
Personalized treatment methods for a complex disease such as cancer benefit from using multiple data...
The release incorporates an end-to-end training and evaluating of a variational autoencoder applied ...
Code base to build Pan Cancer classifiers for any combination of genes or cancer types. This release...
Variational Auto-Encoders are a class of machine learning models that have been used in varying cont...
Information about the dataset files: 1) pancan_rnaseq_freeze.tsv.gz: Publicly available gene expres...
The release tracks recent developments in evaluating tybalt models. The release includes an evaluati...
Cancer has been known as a deadly and complex disease to tackle. By applying machine learning algori...
This dataset includes the harmonised version of all The Cancer Genome Atlas (TCGA) RNA-Seq data (33 ...
Publicly available gene expression dataset from TCGA PanCanAtlas.<div><br></div><div>These data are ...
Abstract: The Cancer Genome Atlas (TCGA) was a large-scale collaborative project initiated by the N...
The UCSC Cancer Genomics Browser (https://genome-cancer.ucsc.edu) offers interactive visualization a...
This is a beta release of workflows for enabling precision medicine to perform neoantigen prediction...
Software to reproduce the analysis for our paper: Predicting drug polypharmacology from cell morphol...
This is the first version of MEGENA co-expression networks and prognostic modules for TCGA pan-cance...
BioBombe analysis applied to gene expression data from The Cancer Genome Atlas (TCGA) PanCanAtlas. ...
Personalized treatment methods for a complex disease such as cancer benefit from using multiple data...
DOI
Add to ORKG