Dr. Kechris' research focuses on the development and application of statistical methods for analyzing omics data. Dr. Kechris has several focus areas: (1) analyzing transcription factor binding and miRNA data to study the regulation of transcription and post-transcriptional processing, (2) examining the genetic and epigenetic factors controlling gene expression, (3) exploring the metabolome, and (4) integrating multiple omics data. Kechris collaborates with investigators studying alcohol abuse using animal models, chronic obstructive pulmonary disease in the COPDGene genetic epidemiology study, and diabetes and obesity in birth cohorts.
Areas of Expertise
- Biostatistics
- Bioinformatics
- Data science
- Genomics
- Chronic obstructive pulmonary disease
Education, Licensure & Certifications
- PhD, Statistics, University of California Berkeley, 2003
- MA, Statistics, University of California Berkeley, 1999
- BS, Applied Mathematics, University of California Los Angeles, 1997
Awards
- Chancellor’s Teaching Recognition Award, University of Colorado Anschutz Medical Campus, 2020
- Fellow, American Statistical Association, 2019
- Excellence in Faculty Research Award, Colorado School of Public Health, 2017
Courses
- BIOS 7731 Advanced Mathematical Statistics I
- BIOS 7659 Statistical Methods in Genomics
Research
- NIH/NHLBI, Multi-omic Networks Associated with COPD progression in TOPMed Cohorts, 2020-2025, Role: Multi-PI (Kechris, Bowler, Lange, Banaei-Kashani)
- NIH/NCI, Addressing Sparsity in Metabolomics Data Analysis, 2018-2022, Role: Multi-PI (Kechris, Ghosh)
- NIH/NHLBI, Biomarker of Lung Disease in African Americans, 2018-2022, Role: Multi-PI (Bowler, Kechris)
Publications and Presentations
- E. Shaddox, C. Peterson, F. Stingo, N. Hanania, C. Cruickshank-Quinn, K. Kechris, R. Bowler and M. Vannucci (2020) Bayesian inference of networks across multiple sample groups and data types. Biostatistics 21:561-576
- E. Mastej, L. Gillenwater, Y. Zhuang, K. Pratte, R. Bowler and K. Kechris (2020) Identifying protein-metabolite networks associated with COPD phenotypes. Metabolites 10:124
- T. Ghosh, W. Zhang, D. Ghosh and K. Kechris (2020) Predictive Modeling for Metabolomics Data. Computational Methods and Data Analysis for Metabolomics in Methods in Molecular Biology Vol 2104 Li S. (ed) Humana, New York, NY
- WJ. Shi, Y. Zhuang, P. Russell, B. Hobbs, M. Parker, P. Castaldi, P. Rudra, B. Vestal, C. Hersh, L. Saba and K. Kechris (2019) Unsupervised discovery of phenotype specific multi-omics networks. Bioinformatics 35:4336-4343
- G. Kordas, P. Rudra, A. Hendricks, L. Saba and K. Kechris (2019) Insight into genetic regulation of miRNA in mouse brain. BMC Genomics 20:849