Inferring gene regulatory networks of ALS from blood transcriptome profiles

Inferring gene regulatory networks of ALS from blood transcriptome profiles

One of the most robust approaches to the prediction of causal driver genes of complex diseases is to apply reverse engineering methods to infer a gene regulatory network (GRN) from gene expression profiles (GEPs). In this work, we analysed 794 GEPs of 1117 human whole-blood samples from Amyotrophic...

Full description

Saved in:
Bibliographic Details
Main Authors: Xena G. Pappalardo, Giorgio Jansen, Matteo Amaradio, Jole Costanza, Renato Umeton, Francesca Guarino, Vito De Pinto, Stephen G. Oliver, Angela Messina, Giuseppe Nicosia
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:Heliyon
Subjects:
Amyotrophic lateral sclerosis (ALS)
Algorithm for the reconstruction of accurate cellular networks - adaptive partitioning version (ARACNe-AP)
Gene expression profile (GEP)
Gene regulatory network (GRN)
Reverse engineering methods
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024167278
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items