Ensemble-based network aggregation improves the accuracy of gene network reconstruction.
Reverse engineering approaches to constructing gene regulatory networks (GRNs) based on genome-wide mRNA expression data have led to significant biological findings, such as the discovery of novel drug targets. However, the reliability of the reconstructed GRNs needs to be improved. Here, we propose...
Main Authors: | Rui Zhong, Jeffrey D Allen, Guanghua Xiao, Yang Xie |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2014-01-01
|
Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC4229114?pdf=render |
Similar Items
-
Improving ECG classification accuracy using an ensemble of neural network modules.
by: Mehrdad Javadi, et al.
Published: (2011-01-01) -
Comparing statistical methods for constructing large scale gene networks.
by: Jeffrey D Allen, et al.
Published: (2012-01-01) -
Ensemble and Greedy Approach for the Reconstruction of Large Gene Co-Expression Networks
by: Francisco Gómez-Vela, et al.
Published: (2019-11-01) -
An Ensemble of Prediction and Learning Mechanism for Improving Accuracy of Anomaly Detection in Network Intrusion Environments
by: Imran, et al.
Published: (2021-09-01) -
ASPEN, a methodology for reconstructing protein evolution with improved accuracy using ensemble models
by: Roman Sloutsky, et al.
Published: (2019-10-01)