Hierarchical decomposition of dynamically evolving regulatory networks

BMC Bioinformatics

Research Article

Dihong Gong¹  Tamer Kahveci¹  Ahmet Ay² 

[1] Department of Computer and Information Science and Engineering, University of Florida, 32611, Gainesville, FL, USA;Departments of Biology and Mathematics, Colgate University, 13346, Hamilton, NY, USA;

关键词: Hierarchy;    Gene regulatory networks;    Network dynamics;   

DOI  :  10.1186/s12859-015-0529-9

 received in 2014-10-27, accepted in 2015-03-09,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundGene regulatory networks describe the interplay between genes and their products. These networks control almost every biological activity in the cell through interactions. The hierarchy of genes in these networks as defined by their interactions gives important insights into how these functions are governed. Accurately determining the hierarchy of genes is however a computationally difficult problem. This problem is further complicated by the fact that an intrinsic characteristic of regulatory networks is that the wiring of interactions can change over time. Determining how the hierarchy in the gene regulatory networks changes with dynamically evolving network topology remains to be an unsolved challenge.ResultsIn this study, we develop a new method, named D-HIDEN (Dynamic-HIerarchical DEcomposition of Networks) to find the hierarchy of the genes in dynamically evolving gene regulatory network topologies. Unlike earlier methods, which recompute the hierarchy from scratch when the network topology changes, our method adapts the hierarchy based on the wiring of the interactions only for the nodes which have the potential to move in the hierarchy.ConclusionsWe compare D-HIDEN to five currently available hierarchical decomposition methods on synthetic and real gene regulatory networks. Our experiments demonstrate that D-HIDEN significantly outperforms existing methods in running time, accuracy, or both. Furthermore, our method is robust against dynamic changes in hierarchy. Our experiments on human gene regulatory networks suggest that our method may be used to reconstruct hierarchy in gene regulatory networks.

【 授权许可】

Unknown   
© Ay et al.; licensee BioMed Central. 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.