Back to search

Article

Unifying the genetic landscape of common and rare diseases via latent neighborhoods

2026-01-28

Abstract excerpt

<h4>ABSTRACT</h4> Resolving disease mechanisms and identifying safer drug targets remains challenging due to difficulties in integrating inconsistent sources of genetic evidence. Here, we developed a deep-learning (DL) method for obtaining latent representations of human diseases and other terms by coupling a variational autoencoder (VAE) to network embeddings from graph representation learning on a protein inter...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
948878c9-3ef2-5785-98ce-4d54f0019c2f
DOI
10.64898/2026.01.27.701945
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Unifying the genetic landscape of common and rare diseases via latent neighborhoodsDOI 10.64898/2026.01.27.701945
Select a neighboring publication to make it the new centre.