NDLI: System Identification and Nonlinear Factor Analysis for Discovery and Visualization of Dynamic Gene Regulatory Pathways

Content Provider	IEEE Xplore Digital Library
Author	Darvish, A. Najarian, K. Jeong, D.H. Ribarsky, W.
Copyright Year	2005
Description	Author affiliation: College of Information Technology, University of North Carolina at Charlotte, Charlotte, NC 28213, adarvish@uncc.edu (Darvish, A.)
Abstract	DNA microarray time-series provide the information vital to estimate the dynamic regulatory pathways and therefore predict the dynamic interaction among genes in time. While dynamic system identification theory has been applied to many fields of study, due to some practical limitations, this theory has been widely used to analyze DNA microarray time series. In this paper, we describe some of these limitations and propose a hierarchical model utilizing nonlinear factor analysis methods to analyze time-series DNA microarray data and identify the dynamic regulatory pathways. The proposed model is applied to model the eukaryotic cell cycle process using a popular dataset of cell cycle time-series. The results indicate that the proposed method can successfully predict the dynamic pathway involved in the process.
Starting Page	1
Ending Page	6
File Size	159629
Page Count	6
File Format	PDF
ISBN	0780393872
DOI	10.1109/CIBCB.2005.1594901
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-15
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	System identification Visualization Nonlinear dynamical systems Biological system modeling DNA Time series analysis Drugs Gene expression Bayesian methods Differential equations
Content Type	Text
Resource Type	Article

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