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(he/him) is a research and associate professor who studies and develops methods to accelerate the development of high-performing crops by identifying specific DNA regions associated with agronomically important traits. He uses statistical approaches for quantitative genetic analyses in crops as well.

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Lipka is a researcher and associate professor passionate about the development of sustainable and high-performing crop practices. In pursuit of this passion, he leads the Lipka Lab at the University of Illinois with the research aim of creating statistical approaches to analyze quantitative genetics data. Lipka's research interests include multidisciplinary collaborations that focus on various genomic-related issues, including the contributions of nonadditive effects to phenotypic variation and the identification of genomic variants associated with agronomic and health-related traits. Some of his research endeavors include the investigation of crop productivity based on the activity of meristems to facilitate further genetic studies and the study into the diversity, genomic complexity, population structure, phylogeny, phylogeography, ploidy, and evolutionary dynamics of switchgrass. Lipka also led a study that developed an R package called Genome Association and Prediction Integrated Tool to handle larger datasets for genome-wide association studies and genomic prediction and selection studies. Prior to joining the University of Illinois, Lipka received his Bachelor of Science in Statistics at the University of Flordia and went on to get his Master of Science and Ph.D. at Purdue University. Lipka was also a postdoctoral associate at Cornell University.

Affiliations:

Dr. Lipka is an associate professor in the  in the  (ACES) at the .

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Illinois scientists to test modernized genetic model for optimized crop breeding

The National Science Foundation (NSF) has funded University of Illinois Urbana-Champaign research that aims to connect the dots between quantitative and molecular genetics and improve crop breeding.
03-Sep-2024 03:05:46 PM EDT

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