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.
I’m a second-year PhD student in the Computational Biology program. Currently, I’m working on a flexible test for detecting selection in present-day population genomic data. I’m also interested in genome-wide scans for genetic effects (i.e., GWAS design) and how to use GWAS towards inferring causal variants.
Github username: 35ajstern (a tribute to Kevin Durant #35’s recent migration to our local NBA team)
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.
S. Negin Mortazavi
I am a visiting postdoctoral scholar recently transplanted into the field of computational biology; my PhD dissertation was on theoretical biomechanics. My current research focus on development and application of machine learning methods and statistical models to cancer genomics.
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 postdoctoral scholar recently graduated from the Computer Science Department at Aarhus University, Denmark. My focus has been on developing mathematical models and software tools in the field of population genetics. As a member of the Nielsen group, I have been developing a suite of methods, under the name Ohana, to infer population structure, estimate phylogenetic trees, and detect selection signals.
I am a P.h.D visiting student from China. I study statistics in Nanjing University of Science and Technology. My main fields is stochastic differential equation. Now I get a project about using Brownian Motion to approximate Wright-Fisher in genetic population from Professor Nielsen.
Casper-Emil Tingskov Pederson
I am a computational biologist from the University of Copenhagen, primarily interested in mammalian genomics, and more specifically how we can tease out historical changes in structure, population size and admixture patterns from genomic data of all sorts.
At Berkeley my focus has been to develop an R-package that can find local admixture patterns in individuals from who we only have low-depth NGS data.
Feel free to email with questions in regard to my research: email@example.com