Quantitative Genetics

Stephen Kachman portrait

Stephen Kachman

Dr. Kachman's research is focused on the development and application of statistical methodology in the area of statistical genomics. Currently he is working on methodology on incorporating genomic information, primarily in the form of SNP genotypes, into national beef cattle evaluation (Matthew Spangler, Department of Animal Science). The statistical methodology development includes extensions based on generalized linear mixed models and Bayesian models. Other projects include genomics of swine reproduction (Daniel Ciobanu, Department of Animal Science, UNL), modeling of the host genetics influence of their gut microbial communities (Andrew Benson, Department of Food Science and Technology, UNL), genetic components of biological responses to stress (Lawrence Harshman, School of Biological Sciences, UNL), and statistical models for the evaluation of teachers and programs (Walter Stroup, Department of Statistics, UNL).

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James Schnable portrait

James Schnable

James Schnable's research group at the University of Nebraska–Lincoln works on developing new methods to combine information from corn, sorghum, and related orphan crops and wild species to identify genetic changes that alter crop traits important to farmers and food traits important to consumers. Working closely with computer scientists, statisticians, engineers, and applied plant breeders his research group develops new quantitative genetic and high throughput phenotyping techniques to analyze novel types of data, including high throughput RGB and hyperspectral imagery collected from plants on a daily basis and parallel genome wide association studies in corn, sorghum and foxtail millet. As part of the Nebraska Food for Health Center, he is working to identify genes in corn and sorghum that alter the biochemical composition of these foods and produce different perturbations of the human gut microbiome when consumed.

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