PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

EPrints submitted by Oliver Stegle

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Number of EPrints submitted by this user: 9

Predicting and understanding the stability of G-quadruplexes
Oliver Stegle, Linda Payet, Jean-Louis Mergny, David J.C. MacKay and Julian L. Huppert
Bioinformatics Volume 25, Number 12, i374-i1382, 2009.

Probabilistic Models in Computational Biology
Oliver Stegle
(2209) PhD thesis, University of Cambridge.

A robust Bayesian two-sample test for detecting intervals of differential gene expression
Oliver Stegle, Katherine J. Denby, Emma J. Cooke, David L. Wild, Zoubin Ghahramani and Karsten Borgwardt
Journal of Compuational Biology 2009.

Discovering Temporal Patterns of Differential Gene Expression in Microarray Time Series
Oliver Stegle, Katherine J. Denby, Stuart McHattie, Andrew Mead, David Wild, Zoubin Ghahramani and Karsten Borgwardt
In: German Conference on Bioinformatics 2009, 28-30 Sept 2009, Halle (Saale).

Accounting for non-genetic factors improves the power of eQTL studies
Oliver Stegle, Anitha Kannan, Richard Durbin and John M. Winn
In: RECOMB 2008, 30 March - 2 April 2008, Singapore.

nference algorithms and learning theory for Bayesian sparse factor analysis
Magnus Rattray, Oliver Stegle, Kevin Sharp and John M. Winn
In: International Workshop on Statistical-Mechanical Informatics 2009(2209).

Association mapping of traits over time using Gaussian processes
Oliver Stegle and Karsten Borgwardt
In: Machine Learning in Computational Biology 2009, Whistler(2009).

A Bayesian framework to account for complex non-genetic factors in gene expression data greatly increases power in eQTL studies .
Oliver Stegle, Leopold Parts, Richard Durbin and John Winn
PLoS Computational Biology Volume 6, Number 5, 2010.

Joint genetic analysis of gene expression data with inferred cellular phenotypes
Leopold Parts, Oliver Stegle, John Winn and Richard Durbin
PLoS Genetics Volume 7, Number 1, 2011.