TY - GEN
T1 - Finding dynamic modules of biological regulatory networks
AU - Ay, Ferhat
AU - Dinh, Thang N.
AU - Thai, My T.
AU - Kahveci, Tamer
PY - 2010
Y1 - 2010
N2 - Often groups of genes in regulatory networks, also called modules, work collaboratively on similar functions. Mathematically, the modules in a regulatory network has often been thought as a group of genes that interact with each other significantly more than the rest of the network. Finding such modules is one of the fundamental problems in understanding gene regulation. In this paper, we develop a new approach to identify modules of genes with similar functions in biological regulatory networks (BRNs). Unlike existing methods, our method recognizes that there are different types of interactions (activation, inhibition), these interactions have directions and they take place only if the activity levels of the activating (or inhibiting) genes are above certain thresholds. Furthermore, it also considers that as a result of these interactions, the activity levels of the genes change over time even in the absence of external perturbations. Here we addresses both the dynamic behavior of gene activity levels and the different interaction types by an incremental algorithm that is scalable to the organism wide BRNs with many dynamic steps. Our experimental results suggest that our method can identify biologically meaningful modules that are missed by traditional approaches.
AB - Often groups of genes in regulatory networks, also called modules, work collaboratively on similar functions. Mathematically, the modules in a regulatory network has often been thought as a group of genes that interact with each other significantly more than the rest of the network. Finding such modules is one of the fundamental problems in understanding gene regulation. In this paper, we develop a new approach to identify modules of genes with similar functions in biological regulatory networks (BRNs). Unlike existing methods, our method recognizes that there are different types of interactions (activation, inhibition), these interactions have directions and they take place only if the activity levels of the activating (or inhibiting) genes are above certain thresholds. Furthermore, it also considers that as a result of these interactions, the activity levels of the genes change over time even in the absence of external perturbations. Here we addresses both the dynamic behavior of gene activity levels and the different interaction types by an incremental algorithm that is scalable to the organism wide BRNs with many dynamic steps. Our experimental results suggest that our method can identify biologically meaningful modules that are missed by traditional approaches.
KW - Dynamic modular structure
KW - Regulatory networks
UR - http://www.scopus.com/inward/record.url?scp=77956156586&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956156586&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2010.31
DO - 10.1109/BIBE.2010.31
M3 - Conference contribution
AN - SCOPUS:77956156586
SN - 9780769540832
T3 - 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010
SP - 136
EP - 143
BT - 10th IEEE International Conference on Bioinformatics and Bioengineering 2010, BIBE 2010
T2 - 10th IEEE International Conference on Bioinformatics and Bioengineering, BIBE-2010
Y2 - 31 May 2010 through 3 June 2010
ER -