Eimear is currently Assistant Professor of Genetics and Genome Science, and a member of the Charles Bronfman Institute for Personalized Medicine, the Institute of Genomics and Multiscale Biology and the Center for Statistical Genetics, at the Icahn School of Medicine at Mount Sinai. The goal of her research is to realize the full potential of genomics to infer human history and evolution and to inform better models for clinical medicine (published in leading research journals including Nature, Science, Cell, Nature Genetics, PNAS and PLoS Genetics). Her recent work (with co-authors) describing a novel variant that causes blond hair in the Solomon Islands, Melanesia, (and published in Science journal) was featured in the New York Times and the Smithsonian NHGRI Human Genome exhibit. When not in the lab, she can be found making a big mess in the kitchen. She recieved a BSc in Biochemistry in Trinity College Dublin, Ireland, and a PhD in Statistical Genetics at Rockefeller University, NY.
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Gillian is a third year graduate student in the Biomedical Sciences PhD program. She is interested in the link between human evolution and history and how that impacts global health and diversity today. She is currenty working on developing methods to detect hidden patterns demography in large urban populations to improve outcomes in genomic medicine. She has applied these methods in a cohort of over 30,000 New Yorkers participating in the BioMe Biobank at the Icahn School of Medicine at Mount Sinai, leading to insights on the population history of communities in New York and the discovery of a genetic variant underlying extreme short stature. She completed her undergraduate at the University of Glasgow in Scotland, where she obtained an M.Sci in Genetics along with various research experience in Molecular Biology.
Amanda is a graduate student in the lab of Dr Eli Stahl and is currently involved in several computational genomics projects involving in-depth genomic analysis across several disciplines including epigenetics, statistical genetics, and population genetics. Specifically, she has analyzed and curated NIH Epigenomics Roadmap data for an analysis of the genetic causes of cardiovascular disease (submitted to PLoS Genetics) and for the design of a sequence project for hyperuricemia and gout disease. More recently, in collaboration with Eimear, Amanda has been working to uncover the genetic architecture of adaptation to high altitude in Native American population from the Andes. This involves the analysis of whole-genome sequence (WGS) data of populations from the Americas in the Thousand Genomes Project and other Native American groups. Amanda has a BA in Microbiology from Cornell University.
Janina is a genetic epidemiologist with special interest in identifying genetic loci that explain disease disparities across populations. She studies a myriad phenotypes, including quantitative cardiovascular traits, anthropometric traits, hematological traits, reproductive outcomes, chronic kidney disease, type 2 diabetes, and pharmacogenomics, in highly structured admixed populations. As a postdoc in the Kenny Lab, she is currently developing methods to extract data from a series of clinical data warehouses to define novel clinical phenotypes, for example extracting real-time physiologic response to short acting catacholamines administered during surgery for pharmacogenomic analyses. She recently presented this work at a platform talk at the 2014 American Society of Human Genetics in San Diego. In addition to this work, she has been using hypothesis-free approaches to detect novel phenotype- genetic ancestry relationships for thousands of clinical diagnoses recorded in the EMR. She chairs and/or participates in genetic analysis working groups in several international consortia such as Genetic Investigation of ANthropometric Traits (GIANT), Population Architecture using Genomics and Epidemiology (PAGE), Electronic Medical Records and Genomics (eMERGE), and the Chronic Kidney Disease Genomics Consortium (CKDGen). Janina recieved a BS in Biology from Spelman College, and an MS in applied statstics and PhD in Human Genetics at Vanderbilt University.
Sumita is a Research Associate in the Kenny lab who has previously worked as a Technician in Albert Einstein College of Medicine's Department of Hematology. She also has experience working in the Therapeutic proteins Unit at Reliance Life Sciences in India. She is currently working on several medical genomics projects in the lab. Sumita received her BSc in Biotechnology and Master of Research (MRes) in Molecular and Cellular Biology from Imperial College London.
Yekaterina (Katya) is a 1st year Graduate Student in the Biomedical Sciences PhD program. She is interested in using our knowledge of genomics to improve clinical care; specifically increasing our understanding and use of clinically relevant variants in the treatment of diverse populations. She has previously worked on the 1000 Genomes Project and ClinGen in her role as a Scientific Program Analyst at the National Human Genome Research Institute. Yekaterina received her BA in Neuroscience from Claremont McKenna College.
Muh-ching (M.C.) has worked as a laboratory manager at Stanford University in the departments of Genetics, Chemical and Systems Biology, Biology and, most recently, the Carnegie Institution for Science. M.C. has leveraged a lifetime of solving the New York Times crossword to her current work playing with the genetic code in genomics and synthetic biology in human, animal and plant systems. She is devising novel methods for targeted resequencing. M.C. received an SB in Chemistry from MIT, and a PhD in Chemistry at UC Berkeley, CA.
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Noura is an assistant professor of genetic and genomic sciences, and faculty member of the Charles Bronfman Institute of Personalized Medicine. She has a translational research focus aiming to improve the diagnosis and treatment of genetic disorders using a combination of electronic medical record data and genomic tools. She is involved in the IGNITE (Implementing GeNomics In pracTicE) Network’s GUARDD (Genetic testing to Understand and Address Renal Disease Disparities) study, which integrates APOL1 genetic testing for kidney disease risk into primary care, and the IPM PGx program, which aims to develop clinical decision support (CDS) and best practices for genome-guided prescribing. She is also a member of the Mount Sinai Genetic Testing Laboratory’s committee that reviews gene mutations discovered in clinical and research projects from next generation sequencing, and has a clinical genetic practice. She collaborates with the Kenny lab on several projects, including the genetics of short stature, the design of the Illumina Mutli-Ethnic Genotype Array and other clinically relevant projects. She completed an M.D./Ph.D. and combined Internal Medicine and Medical Genetics residency program at the the Icahn School of Medicine at Mount Sinai.
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Matt is an assistant professor of anesthesiology and a formally trained computer scientist and cardiac anesthesiologist who has an interest in leveraging large data sets of physiological, clinical, and administrative data to reduce morbidity and mortality and enhance patient safety during the perioperative period. Over the past several years he has designed and implemented a large perioperative data warehouse containing detailed pre-, post-, and intra-operative information, including high resolution physiological data captured from intraoperative monitoring devices, for over 500,000 surgical cases. This dataset continues to grow at a rate of 50,000 cases per year as new case data is automatically added on a real time basis. He collaborates with the Kenny lab on projects to apply genomic approaches in perioperative and acute care settings for genetic discover, improved safty during surgery and for better patient outcomes.
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Carlos is a Professor in the Department of Genetics at Stanford Univerisity, a leading population genetics expert and Eimear's former post-doctoral advisor. They continue to collaborate closely together on several projects to develop statistical, computational and genomic resources for enableing trans- and multi-ethnic studies of complex disease. They are funded co-investigators in a number of NIH large-scale genomics networks, eg PAGE Study.
Chris is currently a post-doc in the Bustamante Lab, and a close collaborator in the Kenny lab. He uses a combination of methods from evolutionary genetics and epidemiology to uncover novel ancestry signals in genetic data and better empower association studies. In the Bustamante Lab, he is continuing his research on broad and fine-scale patterns of ancestry, and he is developing better association study methods that incorporate these important aspects of genetic information. He works with large genetic consortia to develop novel genotyping arrays and interpret findings across different ethnic groups. He is also continuing fieldwork and his interest in mapping traits both in American and Southern African populations.
Gen is a genetic epidemiologist interested in human-pathogen co-evolution, and is a post-doc in the Bustemante lab. She focuses on genetic epidemiology across diverse populations as part of a large genetics consortium while continuing to examine the consequences of selective pressures that pathogens exert upon human populations.