19 open source projects by greenelab

Source code and data analyses for the Sci-Hub Coverage Study

Training and evaluating a variational autoencoder for pan-cancer gene expression data

A collaborative review of the emerging COVID-19 literature. Join the chat here:

Privacy-preserving generative deep neural networks support clinical data sharing

Building classifiers using cancer transcriptomes across 33 different cancer-types

Computational reproducibility using Continuous Integration to produce verifiable end-to-end runs of scientific analysis.

A collaboratively written review paper on deep learning, genomics, and precision medicine

Denoising Autoencoders for Phenotype Stratification

Manuscript describing open collaborative writing with Manubot

R package for normalizing RNA-seq data to make them comparable to microarray data.

An unsupervised transfer learning approach for rare disease transcriptomics

Two or three subtypes of high grade serous ovarian cancer subtypes fit data from different populations better than four

Onboarding materials for the Greene Lab

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.

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously

Extracting biomedical relationships from literature with Snorkel 🏊

Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016

Flexible, probablistic metrics for quality control of scRNA-seq data

Shared Latent Space VAE's