discovering novel biomarkers in RNA-Seq data with tree-based models and survival analysis
-
Updated
Feb 9, 2019 - Python
#
tcga-brca
Here are 6 public repositories matching this topic...
Python project for classification of normal vs tumoral samples using TCGA gene expression data for Scientific Programming Course 2021 (MSc Bioinformatics for Computational Genomics)
-
Updated
Feb 12, 2022 - Jupyter Notebook
A computational framework utilizing Boolean implication networks to decipher asymmetric regulatory logic in 17q-amplified breast cancer, integrating transcriptomic and epigenomic data under BRCA1 stratification.
bioinformatics systems-biology computational-biology transcriptomics breast-cancer r-stats epigenomics multi-omics boolean-networks tcga-brca chromosome-17q brca1
-
Updated
Jan 4, 2026 - R
Multi-task VAE for BRCA cancer detection and PAM50 subtype classification on TCGA/GTEx gene expression, with sparse gene-panel analysis.
bioinformatics tensorflow tcga gene-expression gtex transcriptomics breast-cancer anomaly-detection variational-autoencoder pam50 multitask-learning tcga-brca gene-panels
-
Updated
Dec 13, 2025 - Jupyter Notebook
This project utilizes R as a computational tool to analyze RNA-Seq data from TCGA-BRCA. It identifies differentially expressed genes and enriched pathways between Basal-like and Luminal A breast cancer subtypes.
-
Updated
Jan 8, 2026 - R
Improve this page
Add a description, image, and links to the tcga-brca topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the tcga-brca topic, visit your repo's landing page and select "manage topics."