Back to search

Article

Performance of a Protein Language Model for Variant Annotation in Cardiac Disease

2024-06-05

Abstract excerpt

<h4>Introduction</h4> Genetic testing is a cornerstone in the assessment of many cardiac diseases. However, variants are frequently classified as Variants of Unknown Significance (VUS), limiting the utility of testing. Recently, the DeepMind group (Google, USA) developed AlphaMissense, a unique Artificial Intelligence (AI) based model, based on language model principles for the prediction of missense variant patho...

Topics

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

Identifiers and source

Literature Corpus work
08f8587a-9231-598d-b914-32650311bddb
DOI
10.1101/2024.06.04.24308460
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.
Performance of a Protein Language Model for Variant Annotation in Cardiac DiseaseDOI 10.1101/2024.06.04.24308460
Select a neighboring publication to make it the new centre.