Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bayesian Variable Selection for Probit Mixed Models Applied to Gene
  Selection   In computational biology, gene expression datasets are characterized by very
few individual samples compared to a large number of measurements per sample.
Thus, it is appealing to merge these datasets in order to increase the number
of observations and diversify the data, allowing a more reliable selection of
genes relevant to the biological problem. Besides, the increased size of a
merged dataset facilitates its re-splitting into training and validation sets.
This necessitates the introduction of the dataset as a random effect. In this
context, extending a work of Lee et al. (2003), a method is proposed to select
relevant variables among tens of thousands in a probit mixed regression model,
considered as part of a larger hierarchical Bayesian model. Latent variables
are used to identify subsets of selected variables and the grouping (or
blocking) technique of Liu (1994) is combined with a Metropolis-within-Gibbs
algorithm (Robert and Casella 2004). The method is applied to a merged dataset
made of three individual gene expression datasets, in which tens of thousands
of measurements are available for each of several hundred human breast cancer
samples. Even for this large dataset comprised of around 20000 predictors, the
method is shown to be efficient and feasible. As an illustration, it is used to
select the most important genes that characterize the estrogen receptor status
of patients with breast cancer.

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The categories of this paper are: funct-an
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The categories of this paper are: math-ph
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg
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The categories of this paper are: acc-phys
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The categories of this paper are: chem-ph
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The categories of this paper are: q-fin
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The categories of this paper are: nucl-th
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The categories of this paper are: supr-con
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The categories of this paper are: eess
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The categories of this paper are: hep-ph
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The categories of this paper are: econ
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The categories of this paper are: hep-th
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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: math