The identifiability of gene regulatory networks: the role of observation data

Author(s):  
Xiao-Na Huang ◽  
Wen-Jia Shi ◽  
Zuo Zhou ◽  
Xue-Jun Zhang
2017 ◽  
Vol 39 (3) ◽  
pp. 407-417 ◽  
Author(s):  
Dimple Chudasama ◽  
Valeria Bo ◽  
Marcia Hall ◽  
Vladimir Anikin ◽  
Jeyarooban Jeyaneethi ◽  
...  

2019 ◽  
Vol 11 (7) ◽  
pp. 1723-1729
Author(s):  
Jeffrey A Fawcett ◽  
Hideki Innan

Abstract Nature has found many ways to utilize transposable elements (TEs) throughout evolution. Many molecular and cellular processes depend on DNA-binding proteins recognizing hundreds or thousands of similar DNA motifs dispersed throughout the genome that are often provided by TEs. It has been suggested that TEs play an important role in the evolution of such systems, in particular, the rewiring of gene regulatory networks. One mechanism that can further enhance the rewiring of regulatory networks is nonallelic gene conversion between copies of TEs. Here, we will first review evidence for nonallelic gene conversion in TEs. Then, we will illustrate the benefits nonallelic gene conversion provides in rewiring regulatory networks. For instance, nonallelic gene conversion between TE copies offers an alternative mechanism to spread beneficial mutations that improve the network, it allows multiple mutations to be combined and transferred together, and it allows natural selection to work efficiently in spreading beneficial mutations and removing disadvantageous mutations. Future studies examining the role of nonallelic gene conversion in the evolution of TEs should help us to better understand how TEs have contributed to evolution.


2021 ◽  
Vol 179 (2) ◽  
pp. 205-225
Author(s):  
Roberto Barbuti ◽  
Pasquale Bove ◽  
Roberta Gori ◽  
Damas Gruska ◽  
Francesca Levi ◽  
...  

Gene regulatory networks represent the interactions among genes regulating the activation of specific cell functionalities and they have been successfully modeled using threshold Boolean networks. In this paper we propose a systematic translation of threshold Boolean networks into reaction systems. Our translation produces a non redundant set of rules with a minimal number of objects. This translation allows us to simulate the behavior of a Boolean network simply by executing the (closed) reaction system we obtain. This can be very useful for investigating the role of different genes simply by “playing” with the rules. We developed a tool able to systematically translate a threshold Boolean network into a reaction system. We use our tool to translate two well known Boolean networks modelling biological systems: the yeast-cell cycle and the SOS response in Escherichia coli. The resulting reaction systems can be used for investigating dynamic causalities among genes.


Gene ◽  
2012 ◽  
Vol 501 (2) ◽  
pp. 153-163 ◽  
Author(s):  
Huan Liu ◽  
Qian Yi ◽  
Yi Liao ◽  
Jianguo Feng ◽  
Min Qiu ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document