Computational Genomics Section

  

The Department of Biostatistics’ Section for Bioinformatics and Computational Genomics is a multidisciplinary section dedicated to biological and medical research dealing with ‘omic data. The Section seeks to encourage research and training at the interface between biology, genetics and the mathematical sciences.  

Collaborations: The human genome project is changing the practice of medicine and public health, and genomics is playing an ever more central role in all the biomedical sciences. The advances in our understanding biology and technologies to assess various aspects of the genome, epigenome, transcriptome and proteome present remarkable opportunities for the prevention, treatment and cure of human disease. However, this type of research requires a multidisciplinary team involving clinicians, basic scientists, statistician, bioinformatics and computer science. Our goal is to collaborate with researchers to understand the relationship between complex traits and the genome.

Methodological Research: The research focus of the Section's members focus on novel statistical, bioinformatics and computational approaches for 'omic data to determine the biological and genetic basis of complex traits, including neurological disorders, cancer and pharmacogenomics. The development of state-of-the-art tools will assist researchers with the study design, processing, analysis, interpretation and integration of data across the various 'omes.

Education: The Section seeks to encourage research and training at the interface between biology and the mathematical sciences. The goals of the Section are to:

  • Promote methodological research to develop useful statistical, mathematical, computational and bioinformatics methods and tools for the analysis of genomic data, including Next-Generation Sequence data.
  • Foster the use of innovative analysis methods to address problems in genomic studies of human health and disease
  • Provide interdisciplinary training to students and fellows
  •  Provide educational opportunities, such as formal, university-supported courses and workshops, to educate students and researchers at KUMC as to the available tools in this expanding and challenging field of statistical genomics and bioinformatics.

Collaborations

The University of Kansas Cancer Center

Kansas - INBRE   Click here to see the K-INBRE Summer 2013 Presentation Schedule

Advance Computing Facility at KU-L

 

For questions regarding the section or projects, please contact Dr. Brooke Fridley, bfridley@kumc.edu, 913-945-5039.

For analytical services, please submit your project or grant by clicking the Register Now link.

 

Last modified: Jul 01, 2013
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