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BMCBI
2011
13 years 3 months ago
Empirical Bayesian models for analysing molecular serotyping microarrays
Background: Microarrays offer great potential as a platform for molecular diagnostics, testing clinical samples for the presence of numerous biomarkers in highly multiplexed assay...
Richard Newton, Jason Hinds, Lorenz Wernisch
BMCBI
2006
134views more  BMCBI 2006»
13 years 8 months ago
An approach for clustering gene expression data with error information
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...
Brian Tjaden
BIBE
2004
IEEE
160views Bioinformatics» more  BIBE 2004»
14 years 14 days ago
A Time Series Analysis of Microarray Data
As the capture and analysis of single-time-point microarray expression data becomes routine, investigators are turning to time-series expression data to investigate complex gene r...
Selnur Erdal, Ozgur Ozturk, David L. Armbruster, H...
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
14 years 1 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
BMCBI
2008
101views more  BMCBI 2008»
13 years 8 months ago
Reranking candidate gene models with cross-species comparison for improved gene prediction
Background: Most gene finders score candidate gene models with state-based methods, typically HMMs, by combining local properties (coding potential, splice donor and acceptor patt...
Qian Liu, Koby Crammer, Fernando C. N. Pereira, Da...