tailieunhanh - Báo cáo hóa học: " Research Article Uncovering Gene Regulatory Networks from Time-Series Microarray Data with Variational Bayesian Structural Expectation Maximization"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Uncovering Gene Regulatory Networks from Time-Series Microarray Data with Variational Bayesian Structural Expectation Maximization | Hindawi Publishing Corporation EURASIP Journal on Bioinformatics and Systems Biology Volume 2007 Article ID71312 14 pages doi 2007 71312 Research Article Uncovering Gene Regulatory Networks from Time-Series Microarray Data with Variational Bayesian Structural Expectation Maximization Isabel Tienda Luna 1 Yufei Huang 2 Yufang Yin 2 Diego P. Ruiz Padillo 1 and M. Carmen Carrion Perez1 1 Department of Applied Physics University of Granada 18071 Granada Spain 2 Department of Electrical and Computer Engineering University of Texas at San Antonio UTSA San Antonio tX 78249-0669 USA Received 1 July 2006 Revised 4 December 2006 Accepted 11 May 2007 Recommended by Ahmed H. Tewfik We investigate in this paper reverse engineering of gene regulatory networks from time-series microarray data. We apply dynamic Bayesian networks DBNs for modeling cell cycle regulations. In developing a network inference algorithm we focus on soft solutions that can provide a posteriori probability APP of network topology. In particular we propose a variational Bayesian structural expectation maximization algorithm that can learn the posterior distribution of the network model parameters and topology jointly. We also show how the obtained APPs of the network topology can be used in a Bayesian data integration strategy to integrate two different microarray data sets. The proposed VBSEM algorithm has been tested on yeast cell cycle data sets. To evaluate the confidence of the inferred networks we apply a moving block bootstrap method. The inferred network is validated by comparing it to the KEGG pathway map. Copyright 2007 Isabel Tienda Luna et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION With the completion of the human genome project and successful sequencing genomes of many other organisms emphasis of .

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