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Professor McConkey's lab focuses on complementary areas, utilizing experimental techniques in proteomics analysis and computational bioinformatics approaches to investigate protein function. His research team applies proteomics techniques such as differential in-gel electrophoresis and mass spectrometry to identify changes in protein expression across a variety of biological systems. For example, the lab has employed these approaches for the quantification of cell cycle proteins in yeast, recombinant protein production in mammalian cell lines, and the identification of proteins that mediate plant-bacterial interactions. In addition, computational bioinformatics methods are used to explore protein structure and expression patterns, investigating the functional changes within diverse protein families. Notably, structural pattern recognition algorithms have been applied to predict protein functions including carbohydrate binding and antifreeze activity. These methodologies utilize publicly available high-throughput datasets to map the evolutionary patterns of protein functions among homologous protein groups.
Co-authored with Hajaniriana E and Ruffell S.
Includes fields like Clinical, Cognitive, Developmental, and Industrial/Organizational Psychology.