COMBINING LOCATION AND EXPRESSION DATA FOR PRINCIPLED DISCOVERY OF GENETIC REGULATORY NETWORK MODELS

Author(s):  
ALEXANDER J. HARTEMINK ◽  
DAVID K. GIFFORD ◽  
TOMMI S. JAAKKOLA ◽  
RICHARD A. YOUNG
Author(s):  
D. Ogorelova ◽  
F. Sadyrbaev ◽  
V. Sengileyev

The system of two the first order ordinary differential equations arising in the gene regulatory networks theory is studied. The structure of attractors for this system is described for three important behavioral cases: activation, inhibition, mixed activation-inhibition. The geometrical approach combined with the vector field analysis allows treating the problem in full generality. A number of propositions are stated and the proof is geometrical, avoiding complex analytic. Although not all the possible cases are considered, the instructions are given what to do in any particular situation.


2016 ◽  
Vol 7 ◽  
Author(s):  
José P. Faria ◽  
Ross Overbeek ◽  
Ronald C. Taylor ◽  
Neal Conrad ◽  
Veronika Vonstein ◽  
...  

RSC Advances ◽  
2017 ◽  
Vol 7 (37) ◽  
pp. 23222-23233 ◽  
Author(s):  
Wei Liu ◽  
Wen Zhu ◽  
Bo Liao ◽  
Haowen Chen ◽  
Siqi Ren ◽  
...  

Inferring gene regulatory networks from expression data is a central problem in systems biology.


2007 ◽  
Vol 23 (13) ◽  
pp. i367-i376 ◽  
Author(s):  
Yue Pan ◽  
Tim Durfee ◽  
Joseph Bockhorst ◽  
Mark Craven

2018 ◽  
Vol 457 ◽  
pp. 137-151 ◽  
Author(s):  
Takayuki Ohara ◽  
Timothy J. Hearn ◽  
Alex A.R. Webb ◽  
Akiko Satake

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