Untitled

Abstract

Reverse engineering of gene regulatory networks is an intensively stu-died topic in Systems Biology as it reconstructs regulatory interactions between all genes in the genome in the most complete form. The extre-me computational complexity of this problem and lack of thorough reviews on reconstruction methods of gene regulatory network is a sig-nificant obstacle to further development of this area. In this article the two most common methods for modeling gene regulatory networks are surveyed: Boolean and Bayesian networks. The mathematical descrip-tion of each method is given, as well as several algorithmic approaches to modeling gene networks using these methods; the complexity of al-gorithms and the problems that arise during its implementation are also noted.