Sharlee Climer

Sharlee Climer is an Associate Professor in the Department of Computer Science at the University of Missouri-St. Louis within the College of Arts and Sciences. Her research bridges computational methods with biological applications, focusing on algorithmic solutions for complex biomedical data analysis.

She earned her Ph.D. in Computer Science from Washington University in St. Louis in 2006. Her educational background provides the foundation for her interdisciplinary work at the intersection of computer science and biology.

Dr. Climer's research centers on developing novel computational approaches for biological data, with emphasis on combinatorial optimization and network modeling. Her work tackles Alzheimer's disease mechanisms through genetic fingerprinting and haplotype analysis, while also addressing COVID-19 severity prediction and plasma proteomics. She pioneers data visualization techniques using heatmaps and develops optimization frameworks for clustering algorithms applied to genomic datasets. Her methods reveal hidden patterns in complex traits through innovative combinatorial associations and network exploration.

Her research demonstrates consistent focus on translating computational advances into biomedical insights, particularly through NIH-funded projects targeting Alzheimer's disease pathways and pandemic response. Recent publications show expanding applications into climate science (global climatype clustering) and educational technology, while maintaining core expertise in biomarker discovery and data cleaning methodologies.

Scientific recognition includes:

• National Human Genome Research Institute (NHGRI) LRP awards (2015-present)

As Principal Investigator, she has secured significant external funding including NIH grants for "A Multipronged Interrogation of Large-Scale Omics Data to Reveal COVID-19 Pathways" (2020-2021) and "Using quantitative traits to identify novel genes for Alzheimer’s disease" (2015-2020). Her collaborative work extends to international projects like the Deutsch-Israel ecological genomics grant where she served as Consultant. Her research group actively develops algorithms for biological data analysis with applications spanning neurodegenerative diseases, pandemic response, and climate science.

She maintains active mentorship through office hours in 319 ESH and Zoom, supporting students in computational biology and optimization techniques. Her lab focuses on translating theoretical computer science advances into practical biomedical solutions, with current projects examining Alzheimer's disease subtypes, climate data clustering, and data cleaning frameworks.