Department of Integrative Biology
4098 Valley Life Sciences Building (VLSB)
Berkeley, CA 94720-3140
Phone: (510) 643-4993
My research focuses on developing computational and statistical methods for population genetic analysis. I’m particularly interested in using genomic data to infer pedigrees, with applications in demographic inference and genetic association studies.
As a student in the Computational Biology graduate group, I’m interested in method development for studying tumor evolution using single cell whole genome sequencing, from a population genetics perspective.
I am a PhD candidate in the Graduate Group in Computational Biology. I’m interested in problems that intersect population genetics and applied and theoretical statistics. Prior to graduate school, I studied variation in bacterial translational motif usage in the Amaral Lab at the Northwestern University Institute for Complex Systems. More recently, my thesis research has focused on developing new methods for detecting selective sweeps and inferring demographic models, along with applied population genetics of humans and side-blotched lizards.
I’m interested in studying the evolutionary history of species using genomic data. My current research is focused on humans, using modern and ancient genomic data to learn about our demographic history.
I am a postdoctoral researcher working with the Nielsen lab at U.C. Berkeley and the Sinervo lab at U.C. Santa Cruz. My fields of study include evolutionary biology, behavioral ecology, herpetology, and population genetics. I am particularly interested in questions pertaining to speciation, sexual selection, and the maintenance and loss of polymorphism. My current project in the Nielsen lab is to investigate the genetic basis of the polymorphic mating strategies found in the side-blotched lizard (Uta stansburiana). A major goal of this project is to better understand how specialized mating phenotypes are able to evolve within a species. Please visit my website for more information about my research.
I am a mathematician by training (Master degree from the Moscow State University, 2009; PhD from the University Paris Sud 11, 2013), after my PhD I switched to genomics. My primary research interests include the development of methods for population structure inference, human population genomics, coalescent theory and genealogies. I work on developing a modification of PSMC method (H. Li, R. Durbin 2011) for genotype likelihood data (in collaboration with Thorfinn Sand. For low coverage data, variant calling is not reliable. In this case genotype likelihoods are a better choice to describe the data. I’m also developing a method to estimate migration rates and split times between two populations from distribution of coalescent rates (which can be estimated by PSMC) and joint site frequency spectrum.
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I am a population geneticist interested in developing statistical models to infer demographic history and evolutionary dynamics from DNA sequence data. As a grad student with John Wakeley [link to http://wakeleylab.oeb.harvard.edu/], I worked on a variety of topics involving coalescent theory, including coalescence within fixed pedigrees, coalescent models of identity-by-descent, and inference of reproductive and demographic history in triploid asexual snails using a novel sequentially Markov coalescent model. As a postdoc, with Rasmus Nielsen and Kateryna Makova [link to http://www.bx.psu.edu/makova_lab/] I am using population genetics to understand mitochondrial heteroplasmy, modeling mitochondria as a population that is transmitted between generations from mother to offspring and propagated between diverging cell lineages during development. This work aims to provide insights into the inheritance and phenotypic presentation of mitochondrial disease.
I am a Banting Fellow in the Nielsen lab working on developing better methods to detect introgression in genomic data. My work has focused on understanding the network of hybridization and gene flow occurring within the sunflower genus, Helianthus. More broadly, I aim to quantify the frequency of and implications of hybridization across the tree of life.
I develop mathematical and computational methods to understand recent population dynamics, such as hybridization, sex-specific demography, and human-environment interactions. My work synthesizes modern and ancient genetic data with demographic and environmental records. After a completing a PhD with Noah Rosenberg at Stanford in 2017, I joined the Nielsen lab as a Miller fellow.
Matt’s postdoctoral research is funded by the NSF-PRFB in Biological Collections. He is interested in the genomics of thermal adaptation and water-loss physiology in Puerto Rican anoles. Matt is working with Nielsen Lab (IB), Wang Lab (ESPM), and will be working across museum institutes, including the MVZ.