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

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

Xiaohua Hu, Michael Ng, Fang-Xiang Wu and Bahrad A Sokhansanj
IEEE transactions on information technology in biomedicine, v 13(2), pp 184-194
Mar 2009
PMID: 19272861

Abstract

Markov Chains Algorithms Microarray Analysis Computer Simulation Humans Databases, Genetic Models, Molecular Gene Regulatory Networks Fuzzy Logic Cluster Analysis
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-space modeling, probabilistic Boolean 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.

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12 citations in Scopus

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Information Systems
Computer Science, Interdisciplinary Applications
Mathematical & Computational Biology
Medical Informatics
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