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BMCBI
2008
115views more  BMCBI 2008»
13 years 6 months ago
Principal components analysis based methodology to identify differentially expressed genes in time-course microarray data
Background: Time-course microarray experiments are being increasingly used to characterize dynamic biological processes. In these experiments, the goal is to identify genes differ...
Sudhakar Jonnalagadda, Rajagopalan Srinivasan
EMNLP
2008
13 years 8 months ago
A comparison of Bayesian estimators for unsupervised Hidden Markov Model POS taggers
There is growing interest in applying Bayesian techniques to NLP problems. There are a number of different estimators for Bayesian models, and it is useful to know what kinds of t...
Jianfeng Gao, Mark Johnson
BMCBI
2010
147views more  BMCBI 2010»
13 years 6 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
BMCBI
2005
93views more  BMCBI 2005»
13 years 6 months ago
Two-part permutation tests for DNA methylation and microarray data
Background: One important application of microarray experiments is to identify differentially expressed genes. Often, small and negative expression levels were clipped-off to be e...
Markus Neuhäuser, Tanja Boes, Karl-Heinz J&ou...
JMLR
2010
163views more  JMLR 2010»
13 years 1 months ago
Dense Message Passing for Sparse Principal Component Analysis
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Kevin Sharp, Magnus Rattray