Building classifiers using cancer transcriptomes across 33 different cancer-types
Retrieve and process PubTator annotations
Materials for GCB535 at Penn.
A collaboratively written review paper on deep learning, genomics, and precision medicine
This repository is the home to ADAGEpath R package
Extracting when a compound treats a disease from the literature with Snorkel
Rigor, Reproducibility, Transparency, and Reagent Validity for Computational Biologists
Pipeline to implement a "TAD_Pathways" analysis. Discover candidate genes based on association signals in TADs
DEPRECATED: Integrating topologically associating domains (TADs) to prioritize GWAS signal
Validating glioblastoma immune cell immunohistochemsitry using computational deconvolution of TCGA tumors
Continuous Analysis Example - Performing Differential Expression Analysis with Custom Chip Description Files (CustomCDF)
Using Machine Learning to Identify Glioblastoma patients with NF1 inactivation
Computational reproducibility using Continuous Integration to produce verifiable end-to-end runs of scientific analysis.
Scripts to automate deployment of an adage-server instance
Biological ontologies as hetnets in Neo4j
Three subtypes of HGSC subtypes fit the data better than four
Example of how continuous analysis can be used for RNA-Seq differential expression.
A simple phylogenetic tree building example of Continuous Analysis
Denoising Autoencoders for Phenotype Stratification
Case-control genetics datasets evolved to be epistatic
This is the repository for ADAGE (Analysis using Denoising Autoencoders for Gene Expression)
We play a prediction game in our GCB 535 class. The class aims to teach students, primarily biologists, about machine learning methods and their use. This repository hosts the challenge for individuals outside of our lab.
Scripts and data for re-creating TDM results.
R package for normalizing RNA-seq data to make them comparable to microarray data.
Repository associated with Song et al. manuscript describing a Network-wide Association Study of ADNI Cohorts.
Source code associated with "Leveraging global gene expression patterns to predict expression of unmeasured genes"