Extracting High-Quality Features From Biomedical Datasets Using Multimodal Autoencoders
-
Updated
Mar 20, 2019 - Python
Extracting High-Quality Features From Biomedical Datasets Using Multimodal Autoencoders
This repository contains code for MFmap (model fidelity map), a semi-supervised generative model integrating gene expression, copy number and mutation data, matching cell lines to cancer subtypes. MFmap compresses high dimensional omics data of cell lines and bulk tumours into subtype informative low dimensional latent representations and predic…
Add a description, image, and links to the cancer-subtype topic page so that developers can more easily learn about it.
To associate your repository with the cancer-subtype topic, visit your repo's landing page and select "manage topics."