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 am a PhD candidate in the Department of Statistics. I work broadly in the realm of population genetics, and have been focused on its applications to phylogenetics in recent years. Within phylogenetics I have focused on inference in the presence of mutational variance, and new ways to model the uncertainties of both the coalescent and mutational process. Applications of this research includes divergence time and demography estimation as well as admixture detection.
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 interested in whether climate change can exacerbate emerging infectious disease pressures on wild populations by affecting spatial patterns of genetic diversity. To explore this question, I work with Pleurodema marmoratum in the Cordillera Vilcanota of Southern Peru– the highest-living amphibians in the world!
Diana Aguilar Gómez
I am a PhD Candidate in the Nielsen lab from the Computational Biology Program. I received my undergraduate degree in Genomic Science from the National Autonomous University of Mexico (UNAM). During that time, I worked with sex chromosome evolution and epigenetics. I currently work with skin color adaptation and population history and my main two projects involve color evolution in toad-headed lizards from China and strawberry poison frogs from Panama.
My fields of study include evolutionary biology, behavioral ecology, herpetology, and population genetics. I am particularly interested in questions pertaining to speciation, sexual selection, the maintenance and loss of polymorphism, and the genetic basis of adaptive phenotypes in wild populations. 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. I have also worked on another project with side-blotched lizards that studied the genetic basis of adaptation following plastic changes in coloration in a novel environment. Please visit my website for more information about my research. https://ammoncorl.github.io/
Email: ammoncorl (at) berkeley.edu
I was trained in a rice molecular genetics lab, but got interested in the evolutionary genetic aspects of rice. My research interests include understanding mechanisms and consequences of genetic admixture. Currently, I am using rice genus as a model system to address the potential contribution of gene flow to speciation and domestication. Learning from the genomic pattern of rice domestication, I also work with collaborators to identify and validate new targets for further crop improvement using gene editing technology.
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 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.
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.
I am a postdoc in the Nielsen lab seeking to understand recent human evolution and genetic architecture. I use the UK Biobank data to study ongoing selection, archaic admixture, gene-by-environment interactions, and genetic interactions. For future work, I am interested in jointing statistical genetics with evolutionary genetics. I am also interested in connecting the documented exposures to new environments in the human history with the genetic adaptation through novel/standing variation, or admixture, as well as the associated adaptive and responsive consequences at the molecular, cellular, and organism level.