My research focus is at the interface of Statistics and Computational Biology,
addressing high-dimensional and missing data problems in genomics, especially
relating to gene regulation. I have been involved in the development
of several statistical methods for the discovery of transcription factor
binding sites from DNA sequence in a variety of genomes, ranging from bacteria
to human. I am also interested in the development of Bayesian
methodologies for the elucidation of gene regulatory networks in eukaryotic
genomes combining multiple data types, and feature discovery in high
throughput genomic data from genome tiling arrays. More recently I have been involved in developing Bayesian methods for variable selection in high-dimensional data, in particular relating to the problem of discovery of SNP associations in genome-wide association studies, in which I collaborate with researchers at the Framingham Heart Study in Boston, U.S.A. My other research interests include Bayesian model selection, model-based classification and clustering techniques and statistical inference in hidden Markov and other latent class models.
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