Back to search

Article

<i>CanDrivR-CS</i> : A Cancer-Specific Machine Learning Framework for Distinguishing Recurrent and Rare Variants

2024-09-23

Abstract excerpt

<h4>Motivation</h4> Missense variants play a crucial role in cancer development, and distinguishing between those that frequently occur in cancer genomes and those that are rare may provide valuable insights into important functional mechanisms and consequences. Specifically, if common variants confer growth advantages, they may have undergone positive selection across different patients due to similar selection...

Topics

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

Identifiers and source

Literature Corpus work
ac47c995-7974-5ba2-8a8b-83c0d216fddd
DOI
10.1101/2024.09.19.613896
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.
<i>CanDrivR-CS</i> : A Cancer-Specific Machine Learning Framework for Distinguishing Recurrent and Rare VariantsDOI 10.1101/2024.09.19.613896
Select a neighboring publication to make it the new centre.