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BMCBI
2010
165views more  BMCBI 2010»
13 years 7 months ago
Bayesian integrated modeling of expression data: a case study on RhoG
Background: DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. T...
Rashi Gupta, Dario Greco, Petri Auvinen, Elja Arja...
BMCBI
2004
158views more  BMCBI 2004»
13 years 7 months ago
A novel Mixture Model Method for identification of differentially expressed genes from DNA microarray data
Background: The main goal in analyzing microarray data is to determine the genes that are differentially expressed across two types of tissue samples or samples obtained under two...
Kayvan Najarian, Maryam Zaheri, Ali Ajdari Rad, Si...
JCB
2007
198views more  JCB 2007»
13 years 7 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
BIOINFORMATICS
2005
151views more  BIOINFORMATICS 2005»
13 years 7 months ago
Differential and trajectory methods for time course gene expression data
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Yulan Liang, Bamidele Tayo, Xueya Cai, Arpad Kelem...
NIPS
2003
13 years 9 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...