Intensities measurements of spotted microarrays embody many undesirable systematic variations. Very commonly, varying amounts and types of such variations are observed in different arrays. Although various normalization methods have been proposed to remove such systematic effects, it has not...

The evolution of drug resistance in HIV is characterized by the accumulation of resistance-associated mutations in the HIV genome. Mutagenetic trees, a family of restricted Bayesian tree models, have been applied to infer the order and rate of occurrence of these mutations. Understanding and...

van der Laan and Dudoit (2003) provide a road map for estimation and performance assessment where a parameter of interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using a loss function. After briefly reviewing this approach, this...

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the...

We propose a heuristic approach to the detection of evidence for recombination and gene conversion in multiple DNA sequence alignments. The proposed method consists of two stages. In the first stage, a sliding window is moved along the DNA sequence alignment, and phylogenetic trees are sampled...

We examine the application of statistical model selection methods to reverse-engineering the control of galactose utilization in yeast from DNA microarray experiment data. In these experiments, relationships among gene expression values are revealed through modifications of galactose sugar level...

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the...

Statistical inference of graphical models has become an important tool in the reconstruction of biological networks of the type which model, for example, gene regulatory interactions. In particular, the construction of a score-based Bayesian posterior density over the space of models provides an...

van der Laan and Dudoit (2003) provide a road map for estimation and performance assessment where a parameter of interest is defined as the risk minimizer for a suitable loss function and candidate estimators are generated using a loss function. After briefly reviewing this approach, this...