scholarly journals Reverse engineering genetic networks using nonlinear saturation kinetics

Biosystems ◽  
2019 ◽  
Vol 182 ◽  
pp. 30-41
Author(s):  
Ahammed Sherief Kizhakkethil Youseph ◽  
Madhu Chetty ◽  
Gour Karmakar
2003 ◽  
Vol 31 (6) ◽  
pp. 1516-1518 ◽  
Author(s):  
D. Husmeier

This paper provides a brief introduction to learning Bayesian networks from gene-expression data. The method is contrasted with other approaches to the reverse engineering of biochemical networks, and the Bayesian learning paradigm is briefly described. The article demonstrates an application to a simple synthetic toy problem and evaluates the inference performance in terms of ROC (receiver operator characteristic) curves.


2002 ◽  
Author(s):  
Eugene P. van Someren ◽  
Lodewyk F. A. Wessels ◽  
Marcel J. T. Reinders ◽  
Eric Backer

2010 ◽  
Vol 89 (1) ◽  
pp. 73-80 ◽  
Author(s):  
Luwen Zhang ◽  
Mei Xiao ◽  
Yong Wang ◽  
Wu Zhang

2013 ◽  
Vol 14 (1) ◽  
Author(s):  
Ahsan Raja Chowdhury ◽  
Madhu Chetty ◽  
Nguyen Xuan Vinh

2008 ◽  
Vol 45 ◽  
pp. 161-176 ◽  
Author(s):  
Eduardo D. Sontag

This paper discusses a theoretical method for the “reverse engineering” of networks based solely on steady-state (and quasi-steady-state) data.


2004 ◽  
Vol 62 (12) ◽  
pp. 1057-1063
Author(s):  
A. V. Agranovskiy ◽  
R. E. Agafonov ◽  
R. A. Khadi

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