Back to search

Article

AENetMoX: Fast and Precise scRNA-seq Gene Regulatory Network Inference Through Multi-Modal Feature Integration in Brain Organoids

2026-03-16

Abstract excerpt

Motivation: Gene regulatory network (GRN) inference from single-cell RNA-seq (scRNA-seq) data remains hampered by technical noise, high false-positive rates, and extreme computational costs. Existing methods often require hours or days to process developmental datasets yet fail to capture the physical and topological constraints of regulatory interactions, essential for accurate regulatory mapping. <h4>Results:</h...

Topics

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

Identifiers and source

Literature Corpus work
417985d2-0d19-5b7f-85c6-3cb1dbc10799
DOI
10.20944/preprints202603.1191.v1
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.
AENetMoX: Fast and Precise scRNA-seq Gene Regulatory Network Inference Through Multi-Modal Feature Integration in Brain OrganoidsDOI 10.20944/preprints202603.1191.v1
Select a neighboring publication to make it the new centre.