Genomic analysis of regulatory network dynamics reveals large topological changes

Nature ◽  
2004 ◽  
Vol 431 (7006) ◽  
pp. 308-312 ◽  
Author(s):  
Nicholas M. Luscombe ◽  
M. Madan Babu ◽  
Haiyuan Yu ◽  
Michael Snyder ◽  
Sarah A. Teichmann ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Network Dynamics ◽  
Genomic Analysis ◽  
Topological Changes

scholarly journals Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics

2013 ◽  
Vol 29 (7) ◽  
pp. 910-916 ◽  
Author(s):  
Andrea Ocone ◽  
Andrew J. Millar ◽  
Guido Sanguinetti
Keyword(s):  
Regulatory Network ◽  
Network Dynamics ◽  
Regulatory Models

Visualizing Genome Expression and Regulatory Network Dynamics in Genomic and Metabolic Context

2008 ◽  
Vol 27 (3) ◽  
pp. 887-894 ◽  
Author(s):  
M. A. Westenberg ◽  
S. A. F. T. van Hijum ◽  
O. P. Kuipers ◽  
J. B. T. M. Roerdink
Keyword(s):  
Regulatory Network ◽  
Network Dynamics ◽  
Genome Expression

scholarly journals Dynamic regulatory module networks for inference of cell type specific transcriptional networks

2020 ◽  
Author(s):  
Alireza Fotuhi Siahpirani ◽  
Deborah Chasman ◽  
Morten Seirup ◽  
Sara Knaack ◽  
Rupa Sridharan ◽  
...  
Keyword(s):  
Regulatory Network ◽  
Regulatory Networks ◽  
Network Dynamics ◽  
Cell Types ◽  
Small Sample ◽  
Cell Type ◽  
Regulatory Module ◽  
A Cell ◽  
Cell Type Specific ◽  
Time Point

AbstractChanges in transcriptional regulatory networks can significantly alter cell fate. To gain insight into transcriptional dynamics, several studies have profiled transcriptomes and epigenomes at different stages of a developmental process. However, integrating these data across multiple cell types to infer cell type specific regulatory networks is a major challenge because of the small sample size for each time point. We present a novel approach, Dynamic Regulatory Module Networks (DRMNs), to model regulatory network dynamics on a cell lineage. DRMNs represent a cell type specific network by a set of expression modules and associated regulatory programs, and probabilistically model the transitions between cell types. DRMNs learn a cell type’s regulatory network from input expression and epigenomic profiles using multi-task learning to exploit cell type relatedness. We applied DRMNs to study regulatory network dynamics in two different developmental dynamic processes including cellular reprogramming and liver dedifferentiation. For both systems, DRMN predicted relevant regulators driving the major patterns of expression in each time point as well as regulators for transitioning gene sets that change their expression over time.

scholarly journals Correlated fluctuations carry signatures of gene regulatory network dynamics

2010 ◽  
Vol 266 (3) ◽  
pp. 343-357 ◽  
Author(s):  
Vijayanarasimha H. Pakka ◽  
Adam Prügel-Bennett ◽  
Srinandan Dasmahapatra
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Network Dynamics ◽  
Gene Regulatory

scholarly journals Functional Genomic Analysis of the let-7 Regulatory Network in Caenorhabditis elegans

PLoS Genetics ◽  
2013 ◽  
Vol 9 (3) ◽  
pp. e1003353 ◽  
Author(s):  
Shaun E. Hunter ◽  
Emily F. Finnegan ◽  
Dimitrios G. Zisoulis ◽  
Michael T. Lovci ◽  
Katya V. Melnik-Martinez ◽  
...  
Keyword(s):  
Caenorhabditis Elegans ◽  
Regulatory Network ◽  
Genomic Analysis ◽  
Functional Genomic ◽  
Functional Genomic Analysis
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