My main themes of research are:
Many aspects of computational Biology, for an introduction to the subject,
you can peruse the links and summaries from the course I teach (in
2012 it was in the Spring, in 2013 it will be a summer three week: intensive course):
computational statistics in genetics.
Computer intensive methods in
multivariate statistics, especially the bootstrap.
I wrote my thesis on the bootstrap for multivariate analyses.
I have a course on the bootstrap, if you are interested
here is the web version of the course notes.
Phylogenetic analysis of DNA sequences.
I have several projects linked to this theme in
project, much introductory material can be found at the web site of
course I taught
here is the material associated
Intensive methods in Biology.
More recently see my work on using phylogenetics and multivariate
statistics to study the microbiome.
Multivariate Statistics applied to complex heterogeneous data.
I collaborate with several PI's in the medical school on finding
transcriptomic patterns in genes that are
important in various diseases. For my analyses, I use the
tools made available by the Bioconductor
Combining phylogenetics and multivariate analyses
patterns in the human microbiome. I have developed a reproducible
workflow for the analysis of taxa abundance counts and phylogenetic trees
for making inferences about associations between bacterial
communities and clinical variables. the Bioconductor package
phyloseq is an open source package for documenting and doing
exploratory and confirmatory analyses on microbial census data.
I came to the US for the first time in
1989 to teach a course on Computational Statistics,
a course I have since taught several times and the notes for which
you can find here: Computational Statistics.