Back to search

Article

Inferring large networks with matrix factorisation to capture non-linear dependencies among genes using sparse single-cell profiles

2026-03-10

Abstract excerpt

Inference of non-linear dependencies among a large number of features from their scores is an unresolved challenge. Especially when the feature-score matrix is very sparse, like single-cell transcriptome profiles, the problem of estimating dependencies among a large number of features to infer a network becomes an even more daunting task. Here, we propose a method of network inference in reduced dimension (NIRD) t...

Topics

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

Identifiers and source

Literature Corpus work
4ea8a493-b97c-5dfb-b203-70e72211f200
DOI
10.64898/2026.03.08.710347
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.
Inferring large networks with matrix factorisation to capture non-linear dependencies among genes using sparse single-cell profilesDOI 10.64898/2026.03.08.710347
Select a neighboring publication to make it the new centre.