Mining, modeling, and evaluation of subnetworks from large biomolecular networks and its comparison study

Authors:
Xiaohua Hu;Michael Ng;Fang-Xiang Wu;Bahrad A. Sokhansanj
Affiliations:
College of Information Science and Technology, Drexel University, Philadelphia, PA and Yellow-River Scholar of Henan University, Henan, China;Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong;Division of Biomedical Engineering, Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, Canada;School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA
Venue:
IEEE Transactions on Information Technology in Biomedicine
Year:
2009

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Abstract

In this paper, we present a novel method to mine, model, and evaluate a regulatory system executing cellular functions that can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to such a biomolecular network to obtain various subnetworks. Second, computational models are generated for the subnetworks and simulated to predict their behavior in the cellular context. We discuss and evaluate some of the advanced computational modeling approaches, in particular, state-spacemodeling, probabilisticBoolean network modeling, and fuzzy logic modeling. The modeling and simulation results represent hypotheses that are tested against high-throughput biological datasets (microarrays and/or genetic screens) under normal and perturbation conditions. Experimental results on time-series gene expression data for the human cell cycle indicate that our approach is promising for subnetwork mining and simulation from large biomolecular networks.