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BMCBI
2007
138views more  BMCBI 2007»
13 years 8 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
TCBB
2011
13 years 2 months ago
A Partial Set Covering Model for Protein Mixture Identification Using Mass Spectrometry Data
—Protein identification is a key and essential step in mass spectrometry (MS) based proteome research. To date, there are many protein identification strategies that employ eithe...
Zengyou He, Can Yang, Weichuan Yu
CVPR
2006
IEEE
14 years 10 months ago
Activity Analysis in Microtubule Videos by Mixture of Hidden Markov Models
We present an automated method for the tracking and dynamics modeling of microtubules -a major component of the cytoskeleton- which provides researchers with a previously unattain...
Alphan Altinok, Motaz A. El Saban, Austin J. Peck,...
ICPR
2004
IEEE
14 years 9 months ago
Bayesian Face Recognition Based on Gaussian Mixture Models
Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
Xiaogang Wang, Xiaoou Tang
ICMCS
2007
IEEE
130views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Word Topical Mixture Models for Extractive Spoken Document Summarization
This paper considers extractive summarization of Chinese spoken documents. In contrast to conventional approaches, we attempt to deal with the extractive summarization problem und...
Berlin Chen, Yi-Ting Chen