Research Scientist and Professor
Michael F Hammer is a Research Scientist in the Arizona Research Laboratories Division of Biotechnology at the University of Arizona, with joint appointments in Ecology and Evolutionary Biology, and Anthropology. He received his Ph.D. with Allan C. Wilson at the University of California, Berkeley, USA, and did postdoctoral work with Lee M. Silver at Princeton University, USA, and Richard C. Lewontin at Harvard University. He moved to Arizona in 1991. His laboratory currently conducts research examining genomic diversity in apes (with particular emphasis on contrasting the X chromosome and autosomes) and charactering the genetic basis of epilepsy using 2nd generation sequencing. He also leads a variety of projects that aim to infer population history and natural selection in modern populations using genome-wide data.
Professor of Mathematics
Joe Watkins is Professor of Mathematics and currently serves as the Chair of the Interdisciplinary Program in Statistics. Joe completed his doctoral training at the University of Wisconsin under the direction of Thomas Kurtz. He received a postdoctoral fellowship at the University of British Columbia, supervised by John Walsh. His mathematical training is in probability theory and stochastic processes. He applies this expertise to problems in stochastic modeling and statistical inference of biological phenomena, and has research collaborations with biophysicists, entomologists, bacteriologists, and most notably in geneticists.
"The genetic basis of adaptation to climatic stress in Siberian indigenous populations" The native populations of Siberia provide the best opportunity to investigate the genetic basis of cold resistance given their long-term residence in some of the coldest climates on earth. The combination of dense genetic data, wide geographic population coverage, and several powerful methods for detecting the signatures of natural selection offer the most comprehensive picture of genetic adaptation to cold in humans to date.
"Testing Models of Genetic and Linguistic Change in the Caucasus Mountains" The goal of this project is to examine patterns of genetic diversity of Daghestanian populations at a fine geographic scale and to use a population genetics framework to investigate how historical processes produce genetic, linguistic and cultural change.
"Coevolution of languages and genes in eastern Indonesia" The aim of this project is to investigate the co-evolution of languages and various genetic systems on two islands of eastern Indonesia.
Ph.D Student / Bioinformaticist
B.S. Biochemistry/Neuroscience, Marlboro College, 2001
M.S. Computer Science, University of Arizona, 2011
I am 3rd year PhD student in computer science, coadvised by John Kececioglu and Michael Hammer. My research is diverse. For John I am developing a data structure to do proximity search in metric spaces, while for Michael, my research centers around X chromosome versus autosomal nucleotide diversity, with occasional forays into topics such as using machine learning to clean up 2nd-generation snp calling and demographic inference.
Ph.D Student, Statistics
B.A. Physics/Math, New College of Florida, 2001
M.S. Applied Mathematics, University of Arizona, 2006
My research interests lie at the intersection of population genomics and modern statistics. I am interested in developing novel statistical techniques for inferring demographic history and natural selection from next generation sequencing data. Currently, I am looking for genetic signals of cold adaptation in indigenous Siberian populations.
I received my B.S. in Computer Engineering, M.S. in Electrical Engineering and M.S. in Computational Molecular Biology from National Central University, National Taiwan University, both in Taiwan, and University of Southern California, respectively. I then worked as a statistical genetics associate in Oregon Health & Science University before I joined the labs of Dr. Hammer and Dr. Gutenkunst lab at the University of Arizona. As a Ph.D. student, I am interested in applying and developing computational methods to leverage population level whole genome data for statistical inference of population genetic/genomic questions; specifically, my dissertation is focusing on the inference of the impacts of population demographic processes and natural selection on the molecular levels of the individuals of populations.
My broad interest is using genomics to infer the demographic history of populations. More specifically, I am interested in how the combination of drift and admixture affect inference of these processes. My research focuses on making methodological improvements to inferring the history of these processes when using SNP array data as well as inferring the forces that contributed to population differentiation in two human population isolates.
Consuelo Dayzu Quinto
My current project focuses on understanding the peopling of Japan using single nucleotide polymorphisms (SNPs) and Approximate Bayesian Computation (ABC). Japan has an interesting history from the point of view of population genetics, and three hypotheses exist regarding its peopling. The hybridization theory is the best supported by previous genetics studies of the studies of the Y chromosome and DNA mitochondrial; however genome-wide polymorphisms have not been used to answer this question. This theory argues that modern Japanese are the result of an admixture process between the Jomon and Yayoi people, two groups that are known to have migrated to the archipelago at different times and developed distinct cultures.
Broadly, I'm interested in the genetics of human disease, and in the Hammer Lab, I study the genetics of epilepsy. One of my projects is investigating the role of modifier genes in Dravet Syndrome (DS), an intractable form of epilepsy with a strong genetic basis. About 70% of DS is caused by mutations in the SCN1A gene, but there is a range of phenotypic heterogeneity that may be explained other contributing genetic factors. My goal is to use whole exome sequence data from patients with DS and look for evidence of variants that contribute to the phenotype.
Although my training was in biology (B.S. in EEB), I have done computer-aided data analysis for several different labs, first in neuroscience, and now in genetics. I enjoy finding or developing methods to extract the most important information from large data sets. My current focus is on whole exome sequencing of parent-child trios to identify potential causes of sporadic disease in the child. However, I enjoy being involved in the many projects that come through the Hammer lab and the University of Arizona Genetics Core facility, where I also work. These projects have included de novo assembly of bacterial genomes, RNA-Seq from insect tissues, and whole genome analysis of non-human primates. My favorite programming languages are perl and R, but I want to learn python soon.
I do computational work in the lab. I write computer code to check/prepare experimental data for statistical analysis, find inconsistencies in experimental data and calculate summary stats. Another part of my work is searching public databases for new datasets. I write code to make public data sets more pretty and user friendly for us. Currently I work for the Daghestan project. I help to analyze SNP chip data from samples from Daghestan and compare it with data from other geographical regions. My favorite computer languages are Perl and Perl/Tk, although for some projects I use R and Matlab.
My research is focused on understanding causes of human hereditary disorders and promoting preventive measures to lower incidence of such conditions in the future. Having expertise in computational biology and bionformatics helps me to achieve these goals. I have extended experience processing next generation sequencing (NGS) data in a wide spectrum of projects involving Rna-Seq, 16S microbiome profiling, de novo assembly of various genomes and variants calling. I spend most of my time working at the University of Arizona Genetics Core, where I process NGS found genetic variants in the context of existing databases (evolutionary conservation scores, human population frequencies, disease association, deleterious impact predictions and variants annotations). Our current projects extensively depend on proper database design and management, which mandates fluency in SQL and Java languages on my side. Finding disease causing variants leading to rare disease (following simple recessive, de novo, X-linked, compound heterozygous) is a challenging task. Our group has recently started investigating genetic lesions leading to various forms of cancer to better navigate patient's treatment.