The Bioinformatics Lab

Home People Publications Projects Courses Funding Contact Archive

Identification of Dynamic Functional Modules in Biological Regulatory Networks

The modules in a regulatory network has often been thought as a group of genes that interact among each other more than with the rest of network. This traditional approach however have several drawbacks. First, the impact of an interaction depends on the type of the interaction (i.e., activation or inhibition) as well as the topology of all the other interactions in the network. Second, the ability of each interaction to take place depends on the activity levels of the set of genes that take part in it. Furthermore, the activity levels of the genes can change over time due to these interactions. As a result, existing module identification methods often fail to cluster functionally similar genes and they can not adopt to the changing activity levels of the genes. In this paper, we develop a new approach to identify dynamic modules in biological regulatory networks. Unlike existing methods, we consider the activity levels, interaction types and the topologies of the networks to compute the impact of each gene on the state of the network.We put two genes in the same module only if they have similar impacts on the state of the network. We name these modules “functional modules”. We also devise an adaptive algorithm to quickly detect and update the modular structure of the network as the activity levels of the genes change over time. Our experiments show that our method can find biologically meaningful modules that are missed by traditional approaches. Also, our adaptive method is an order of magnitude faster than the traditional approach.
Download the software for functional modules identification in biological regulatory networks

Tamer Kahveci
Last modified: Tue Sep 22 12:30:01 EDT 2009