Back to search

Article

Predicting Clinical Phenotypes by Growth Curve Modeling of Transcriptomic Signatures during Disease Progression

2026-01-15

Abstract excerpt

High-throughput transcriptomic analysis has benefited from many statistical tests of differential gene expression across two or more groups such as t tests, ANOVA, etc. Yet, in complex transcriptomic datasets such as multi-group longitudinal measures, few studies have addressed such key issues as group effects and temporal dependency in expression profiles with a single model that is both practically effective an...

Topics

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

Identifiers and source

Literature Corpus work
c6557cf6-05cd-5c67-95fe-cc6acb08c860
DOI
10.64898/2026.01.13.699292
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 10 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.
Predicting Clinical Phenotypes by Growth Curve Modeling of Transcriptomic Signatures during Disease ProgressionDOI 10.64898/2026.01.13.699292
Select a neighboring publication to make it the new centre.