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» A new approach to analyzing gene expression time series data
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RECOMB
2002
Springer
14 years 9 months ago
A new approach to analyzing gene expression time series data
We present algorithms for time-series gene expression analysis that permit the principled estimation of unobserved timepoints, clustering, and dataset alignment. Each expression p...
Ziv Bar-Joseph, Georg Gerber, David K. Gifford, To...
BIOCOMP
2006
13 years 10 months ago
Dynamic Bayesian Network (DBN) with Structure Expectation Maximization (SEM) for Modeling of Gene Network from Time Series Gene
Exploring gene regulatory network is a key topic in molecular biology. In this paper, we present a new dynamic Bayesian network (DBN) framework embedded with structural expectatio...
Yu Zhang, Zhidong Deng, Hongshan Jiang, Peifa Jia
BMCBI
2007
144views more  BMCBI 2007»
13 years 9 months ago
Spectral estimation in unevenly sampled space of periodically expressed microarray time series data
Background: Periodogram analysis of time-series is widespread in biology. A new challenge for analyzing the microarray time series data is to identify genes that are periodically ...
Alan Wee-Chung Liew, Jun Xian, Shuanhu Wu, David K...
BIOINFORMATICS
2004
62views more  BIOINFORMATICS 2004»
13 years 9 months ago
Analyzing time series gene expression data
Ziv Bar-Joseph
BMCBI
2008
148views more  BMCBI 2008»
13 years 9 months ago
BATS: a Bayesian user-friendly software for Analyzing Time Series microarray experiments
Summary: BATS is a user-friendly software for Bayesian Analysis of Time Series microarray experiments based on the novel, truly functional and fully Bayesian approach proposed in ...
Claudia Angelini, Luisa Cutillo, Daniela De Candit...