Document Type

Journal Article

Department/Unit

Department of Mathematics

Title

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

Language

English

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-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. © 2009 IEEE.

Keywords

Biomolecular network analysis, Fuzzy modeling, Probabilistic Boolean network (PBN) model, State-space model subnetwork mining

Publication Date

2009

Source Publication Title

IEEE Transactions on Information Technology in Biomedicine

Volume

13

Issue

2

Start Page

184

End Page

194

Publisher

Institute of Electrical and Electronics Engineers

DOI

10.1109/TITB.2008.2007649

Link to Publisher's Edition

http://dx.doi.org/10.1109/TITB.2008.2007649

ISSN (print)

10897771

ISSN (electronic)

15580032

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