Automated Large-Scale Control of Gene Regulatory Networks

Tan, Mehmet
Alhajj, Reda
Polat, Faruk
Controlling gene regulatory networks (GRNs) is an important and hard problem. As it is the case in all control problems, the curse of dimensionality is the main issue in real applications. It is possible that hundreds of genes may regulate one biological activity in an organism; this implies a huge state space, even in the case of Boolean models. This is also evident in the literature that shows that only models of small portions of the genome could be used in control applications. In this paper, we empower our framework for controlling GRNs by eliminating the need for expert knowledge to specify some crucial threshold that is necessary for producing effective results. Our framework is characterized by applying the factored Markov decision problem ( FMDP) method to the control problem of GRNs. The FMDP is a suitable framework for large state spaces as it represents the probability distribution of state transitions using compact models so that more space and time efficient algorithms could be devised for solving control problems. We successfully mapped the GRN control problem to an FMDP and propose a model reduction algorithm that helps find approximate solutions for large networks by using existing FMDP solvers. The test results reported in this paper demonstrate the efficiency and effectiveness of the proposed approach.


Dynamic information handling in continuous time Boolean Network model of gene interactions
Öktem, Hakan (Elsevier BV, 2008-08-01)
Growing information and knowledge on gene regulatory networks, which are typical hybrid systems, has led a significant interest in modeling those networks. An important direction of gene network modeling is studying the abstract network models to understand the behavior of a class of systems. Boolean Networks has emerged as an important model class on this direction. Limitations of traditional Boolean Networks led the researchers to propose several generalizations. In this work, one such class, the Continuo...
Induction and control of large-scale gene regulatory networks
Tan, Mehmet; Tan, Mehmet; Department of Computer Engineering (2009)
Gene regulatory networks model the interactions within the cell and thus it is essential to understand their structure and to develop some control mechanisms that could effectively deal with them. This dissertation tackles these two aspects. To handle the first problem, a new constraint-based modeling algorithm is proposed that can both increase the quality of the output and decrease the computational requirements for learning the structure of gene regulatory networks by integrating multiple biological data...
Feature reduction for gene regulatory network control
Tan, Mehmet; Polat, Faruk; Alhajj, Reda (2007-10-17)
Scalability is one of the most important issues in control problems, including the control of gene regulatory networks. In this paper we argue that it is possible to improve scalability of gene regulatory networks control by reducing the number of genes to be considered by the control policy; and consequently propose a novel method to estimate genes that are less important for control. The reported test results on real and synthetic data demonstrate the applicability and effectiveness of the proposed approach.
An Investigation of Link Quality Assessment for Mobile Multi-hop and Multi-rate Wireless Networks
Zhou, Jinglong; Jacobsson, Martin; Onur, Ertan; Niemegeers, Ignas (Springer Science and Business Media LLC, 2012-07-01)
Wireless ad hoc networks will be an important component in future communication systems. The performance of wireless ad hoc networks can be improved by link quality-aware applications. Wireless link quality is dynamic in nature, especially in mobile scenarios. Therefore, accurate and fast packet delivery ratio estimation is a prerequisite to good performance in mobile, multi-hop and multi-rate wireless ad hoc networks. In this paper, we propose a novel packet delivery ratio estimation method that improves t...
Controlling discrete genetic regulatory networks
Abul, Osman; Polat, Faruk; Department of Computer Engineering (2005)
Genetic regulatory networks can model dynamics of cells. They also allow for studying the effect of internal or external interventions. Selectively applying interventions towards a certain objective is known as controlling network dynamics. In this thesis work, the issue of how the external interventions af fect the network is studied. The effects are determined using differential gene expression analysis. The differential gene expression problem is further studied to improve the power of the given method. ...
Citation Formats
M. Tan, R. Alhajj, and F. Polat, “Automated Large-Scale Control of Gene Regulatory Networks,” IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, pp. 286–297, 2010, Accessed: 00, 2020. [Online]. Available: