Reconstruct a Transcriptional Regulatory Network using the principle of Maximum Entropy.
-
Updated
Mar 30, 2017 - Julia
Reconstruct a Transcriptional Regulatory Network using the principle of Maximum Entropy.
Gene expression experiments using Python and R
Homework Machine Learning
An R package to create gene expression atlases from bulk RNA-seq data on NCBI SRA
"DNA methylation and gene expression integration in cardiovascular disease"
TRANSCRIPTOMICS & METABOLOMICS: Gene expression modules vs. metabolites modules correlation using WGCNA R package.
MassGEM_Plot can visualize the expression of a large number of genes at the same time
The provided set of bash scripts constitutes a comprehensive RNA-seq analysis workflow, facilitating the processing and analysis of high-throughput sequencing data.
To perform RNA-Seq data analysis and calculate length-scaled transcripts per million (TPM) values using the Salmon tool and the GenomicFeatures package in R.
R script for predicting the ubiquitin by gene expression matrix
Data science project work with genomics/biological data
Co-expression networks for gene correlation analysis.
This repository includes code and a pre-trained model of scHiGex for single-cell gene expression prediction.
Machine learning for Project Cognoma
An R package to impute miRNA activity using protein-coding gene expression
Software for intuitively doing Differential Gene Expression (DGE) analysis on Windows and GNU\Linux, based on R packages.
End-to-end ensemble model that integrates several neural networks trained on distinct features with attention mechanism.
Code to reproduce analyses in Iron Responsive Element (IRE)-mediated responses to iron dyshomeostasis in Alzheimer’s disease (Hin et al.)
Add a description, image, and links to the gene-expression topic page so that developers can more easily learn about it.
To associate your repository with the gene-expression topic, visit your repo's landing page and select "manage topics."