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BMCBI
2008
115views more  BMCBI 2008»
14 years 9 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
14 years 11 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»
14 years 9 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»
14 years 9 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»
14 years 4 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