Back to search

Article

Using Networks and Prior Knowledge to Uncover novel Rare Disease Phenotypes

2025-04-03

Abstract excerpt

Rare diseases are characterized by low prevalence and high phenotypic diversity. Accurately identifying phenotypes associated with rare diseases is crucial for facilitating their diagnosis and management. However, this task presents significant challenges: rare disease datasets are typically small, making statistical assessments difficult, and they often report phenotypes using various terminologies, hindering the...

Topics

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

Identifiers and source

Literature Corpus work
1d208d0b-cb77-5d94-80e0-ee38d0665cbe
DOI
10.1101/2025.04.02.25325098
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.
Using Networks and Prior Knowledge to Uncover novel Rare Disease PhenotypesDOI 10.1101/2025.04.02.25325098
Select a neighboring publication to make it the new centre.