Browsing by Author "Dunson, David B"
Now showing items 1-13 of 13
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A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice.
(Front Behav Neurosci, 2016)Development of proficient spoken language skills is disrupted by mutations of the FOXP2 transcription factor. A heterozygous missense mutation in the KE family causes speech apraxia, involving difficulty producing words ... -
Bayesian Gaussian Copula Factor Models for Mixed Data.
(J Am Stat Assoc, 2013-06-01)Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent ... -
Bayesian inference for genomic data integration reduces misclassification rate in predicting protein-protein interactions.
(PLoS Comput Biol, 2011-07)Protein-protein interactions (PPIs) are essential to most fundamental cellular processes. There has been increasing interest in reconstructing PPIs networks. However, several critical difficulties exist in obtaining reliable ... -
Bayesian network-response regression.
(Bioinformatics, 2017-01-06)Motivation: There is increasing interest in learning how human brain networks vary as a function of a continuous trait, but flexible and efficient procedures to accomplish this goal are limited. We develop a Bayesian ... -
Data augmentation for models based on rejection sampling.
(Biometrika, 2016-06)We present a data augmentation scheme to perform Markov chain Monte Carlo inference for models where data generation involves a rejection sampling algorithm. Our idea is a simple scheme to instantiate the rejected proposals ... -
Efficient Gaussian process regression for large datasets.
(Biometrika, 2013-03)Gaussian processes are widely used in nonparametric regression, classification and spatiotemporal modelling, facilitated in part by a rich literature on their theoretical properties. However, one of their practical limitations ... -
Generalized admixture mapping for complex traits.
(G3 (Bethesda), 2013-07-08)Admixture mapping is a popular tool to identify regions of the genome associated with traits in a recently admixed population. Existing methods have been developed primarily for identification of a single locus influencing ... -
Joint eQTL assessment of whole blood and dura mater tissue from individuals with Chiari type I malformation.
(BMC Genomics, 2015-01-22)BACKGROUND: Expression quantitative trait loci (eQTL) play an important role in the regulation of gene expression. Gene expression levels and eQTLs are expected to vary from tissue to tissue, and therefore multi-tissue analyses ... -
Latent Stick-Breaking Processes.
(J Am Stat Assoc, 2010-04-01)We develop a model for stochastic processes with random marginal distributions. Our model relies on a stick-breaking construction for the marginal distribution of the process, and introduces dependence across locations by ... -
Male mice song syntax depends on social contexts and influences female preferences
(FRONTIERS IN BEHAVIORAL NEUROSCIENCE, 2015-04-01) -
Methodologic and statistical approaches to studying human fertility and environmental exposure.
(Environ Health Perspect, 2004-01)Although there has been growing concern about the effects of environmental exposures on human fertility, standard epidemiologic study designs may not collect sufficient data to identify subtle effects while properly adjusting ... -
Multichannel electrophysiological spike sorting via joint dictionary learning and mixture modeling
(IEEE Transactions on Biomedical Engineering, 2014-01-01)We propose a methodology for joint feature learning and clustering of multichannel extracellular electrophysiological data, across multiple recording periods for action potential detection and classification (sorting). Our ... -
Nonparametric Bayes Conditional Distribution Modeling With Variable Selection.
(J Am Stat Assoc, 2009-12-01)This article considers a methodology for flexibly characterizing the relationship between a response and multiple predictors. Goals are (1) to estimate the conditional response distribution addressing the distributional ...
