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Quantitative Omics (QOC) Core

The goal of the Quantitative Omics Core (QOC) is to develop and apply innovative statistical, bioinformatics and data science methods to assist the research activities of Kansas Institute of Precision Medicine investigators. We offer help with:

  • study design
  • data management
  • data visualization
  • bioinformatics
  • access to high-performance computing
  • state-of-the-art bioinformatics software

We have experience in the analysis and interpretation of high-throughput ‘omic studies, including studies of gene expression (microarray and RNA-seq), pathway analysis, protein-DNA binding (e.g. ChIP-seq), DNA methylation, DNA variation and integrative multi-‘omic analysis.

Core Team

Our directors have extensive experience in the development and application of statistical methods for large-scale ‘omic data and other biomedical “big-data”.

  • Devin Koestler, Ph.D., Professor and Associate Director of Research Operations, Department of Biostatistics & Data Science
  • Jeffrey Thompson, Ph.D., Associate Professor, Department of Biostatistics & Data Science, Chief Research Informatics Officer, The University of Kansas Health System
  • Mihaela Sardiu, Ph.D., Associate Professor, Department of Biostatistics & Data Science

The core also includes:

  • Prabhakar Chalise, Ph.D., Associate Professor, Department of Biostatistics & Data Science
  • Zhigou Zhou, Ph.D., Assistant Professor, Department of Biostatistics & Data Science
  • Dong Pei, Ph.D., Assistant Professor, Department of Biostatistics & Data Science
  • bioinformatics specialists, Emily Nissen, M.S., and Rachel Griffard, M.S.

QOC Core members have a diverse and complementary skillset, with expertise that spans data sciences, biostatistics, bioinformatics, statistical omics, machine/deep learning, artificial intelligence (AI), integrated analysis of multi-omic data, and analysis of high-dimensional data. In addition to a boasting strong track-record of team-science based collaboration, QOC Core members are active contributors to novel data science methodologies. Together with access to high-performance computing and storage for large data sets, this core helps KIPM investigators with their study design, data collection, data management, analytics, bioinformatics and statistical needs.

Contact

For more information about the Omics core resources, contact KIPM_COBRE@kumc.edu.