scholarly journals A Novel Data-Driven Boolean Model for Genetic Regulatory Networks

2018 ◽  
Vol 9 ◽  
Author(s):  
Leshi Chen ◽  
Don Kulasiri ◽  
Sandhya Samarasinghe
2007 ◽  
Vol 4 (3) ◽  
pp. 1-14 ◽  
Author(s):  
Richard Banks ◽  
L. Jason Steggles

Summary To understand the function of genetic regulatory networks in the development of cellular systems, we must not only realise the individual network entities, but also the manner by which they interact. Multi-valued networks are a promising qualitative approach for modelling such genetic regulatory networks, however, at present they have limited formal analysis techniques and tools. We present a flexible formal framework for modelling and analysing multi-valued genetic regulatory networks using high-level Petri nets and logic minimization techniques. We demonstrate our approach with a detailed case study in which part of the genetic regulatory network responsible for the carbon starvation stress response in Escherichia coli is modelled and analysed. We then compare and contrast this multivalued model to a corresponding Boolean model and consider their formal relationship.


2012 ◽  
Vol 18 (4) ◽  
pp. 385-397 ◽  
Author(s):  
Larry Bull

This short article presents an abstract, tunable model of genomic structural change within the cell life cycle and explores its use with simulated evolution. A well-known Boolean model of genetic regulatory networks is extended to include changes in node connectivity based upon the current cell state to begin to capture some of the effects of transposable elements. The evolvability of such networks is explored using a version of the NK model of fitness landscapes with both synchronous and asynchronous updating. Structural dynamism is found to be selected for in nonstationary environments with both update schemes and subsequently shown capable of providing a mechanism for evolutionary innovation when such reorganizations are inherited. This is also found to be the case in stationary environments with asynchronous updating.


2012 ◽  
Vol 18 (2) ◽  
pp. 223-236 ◽  
Author(s):  
Larry Bull

This article presents an abstract, tunable model containing two of the principal information-processing features of cells and explores its use with simulated evolution. The random Boolean model of genetic regulatory networks is extended to include a protein interaction network. The underlying behavior of the resulting two coupled dynamical networks is investigated before their evolvability is explored using a version of the NK model of fitness landscapes.


2019 ◽  
Vol 356 (5) ◽  
pp. 2847-2869 ◽  
Author(s):  
Dandan Yue ◽  
Zhi-Hong Guan ◽  
Juan Li ◽  
Feng Liu ◽  
Jiang-Wen Xiao ◽  
...  

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