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» Using Bayesian networks to analyze expression data
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AINA
2008
IEEE
15 years 4 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
92
Voted
BMCBI
2010
129views more  BMCBI 2010»
14 years 9 months ago
A temporal precedence based clustering method for gene expression microarray data
Background: Time-course microarray experiments can produce useful data which can help in understanding the underlying dynamics of the system. Clustering is an important stage in m...
Ritesh Krishna, Chang-Tsun Li, Vicky Buchanan-Woll...
BMCBI
2007
168views more  BMCBI 2007»
14 years 9 months ago
Bayesian model-based inference of transcription factor activity
Background: In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is co...
Simon Rogers, Raya Khanin, Mark Girolami
NAR
2002
141views more  NAR 2002»
14 years 9 months ago
Co-expression pattern from DNA microarray experiments as a tool for operon prediction
The prediction of operons, the smallest unit of transcription in prokaryotes, is the first step towards reconstruction of a regulatory network at the whole genome level. Sequence ...
Chiara Sabatti, Lars Rohlin, Min-Kyu Oh, James C. ...
ICASSP
2009
IEEE
15 years 4 months ago
Robust cross-race gene expression analysis
This paper develops a Bayesian network (BN) predictor to profile cross-race gene expression data. Cross-race studies face more data variability than single-lab studies. Our desig...
Hsun-Hsien Chang, Marco Ramoni