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My research aims to improve our understanding of the evolutionary processes that shape
genomes and genomic function, and examine the role of neutral drift and natural selection
in this process.
The main focus of my work is to develop new computational methods that
generate reliable evolutionary inferences from high throughput sequencing data.
My methods are based on mathematical models of molecular evolution, population genetics,
and phylogenetics, and they are designed and implemented using efficient algorithmic
techniques.
I am particularly interested in using the computational methods I develop to
resolve
key open questions in human population genetics
and to shed new light on
evolution of function in the human genome.
I also maintain an active thread of research devoted to theoretical aspects of evolution
and algorithms for phylogenetic inference.
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- Arbiza L, Gronau I, Aksoy BA, Hubisz MJ, Gulko B, Keinan A, Siepel A.
Genome-wide inference of natural selection on human transcription factor binding sites.
Nature Genetics, accepted April 3, 2013.
- Gronau I, Arbiza L, Mohammed J, Siepel A.
Inference of Natural Selection from Interspersed Genomic Elements Based on Polymorphism and Divergence.
Mol Biol Evol, in print, 2013. doi: 10.1093/molbev/mst019
- Gronau I, Moran S, Snir S.
Fast and Reliable Reconstruction of Phylogenetic Trees with Indistinguishable Edges.
Random Struct Alg 40(3):350-384, 2012
* Extended Abstract published in
SODA, 2008
- Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A.
Bayesian inference of ancient human demography from individual genome sequences.
Nature Genetics 43:1031-1034, 2011
- Gronau I, Moran S, Yavneh I.
Towards Optimal Distance Functions for Stochastic Substitutions Models.
J Theor Biol 260:294-307, 2009
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