Our Assets: University of Kansas Medical Center
For more info, visit the University of Kanas Medical Center website
Devin Koestler, PhD
Dr. Koestler’s research involves the development and application of bioinformatics/statistical methodologies for analyzing high-throughput ‘omic’ data. He also has interests in epigenetics and molecular epidemiology, specifically DNA methylation and its implications for human health and disease. In addition to his methodological interests, which include, multivariate statistics, mixture models, and mixed-effects models, he is also collaborating in the areas of environmental health, the human microbiome, and a wide variety of different epigenetics studies. The shared theme across his collaborative research projects is the use of high-dimensional genomic data to gain further insight into some biological process.
Peter Smith, PhD
Dr. Smith’s research examines this interplay between nerve and target and the factors that govern neuronal growth and degeneration. He is especially interested in how this relationship is affected by gonadal steroid hormones such as estrogen. Ongoing projects examine mechanisms and consequences of neuroplasticity in peripheral tissues including: reorganization of cardiac innervation following myocardial infarction, which may contribute to sudden cardiac death; estrogen-induced remodeling of innervation of the reproductive tract; mechanisms by which nerve projections are pruned under normal and pathophysiological conditions; and the role of estrogen in the etiology of female pain syndromes. Dr. Smith is the Director of KUMC’s Bioinformatics core.
Linux x86 64 Cluster
- 3 nodes with 8-core and 48GB memory each
Linux x86 64 servers
- 12-core with 72GB memory
- 24-core with 128GB memory
- 12-core with 144GB memory
40TB Data Storage
We use a number of open-source software packages such as R for data processing and analysis. Licenses of proprietary software are as follows.
- Bioinformatics Toolbox
- Computer Vision System Toolbox
- Curve Fitting Toolbox
- DSP System Toolbox
- Fixed-Point Toolbox
- Image Processing Toolbox
- Neural Network Toolbox
- Optimization Toolbox
- Parallel Computing Toolbox
- Signal Processing Toolbox
- Statistics Toolbox
- Wavelet Toolbox
Partek Genomics Suite
Acumenta The Literature LabTM
CLC Genomics Workbench
We provide a variety of services in bioinformatics and computational biology. Some of these services are listed below. Please feel free to contact the Bioinformatics Core for more information on these services. The Bioinformatics Core will also be happy to discuss with you the feasibility of supporting customer applications specific to your research.
- RNA-Seq: provides an unbiased deep coverage and base level resolution of the whole transcriptome. Has a low background signal and does not have an upper limit of quantification.
- Chip-Seq: combines chromatin immunoprecipitation with high-throughput sequencing to provide an unbiased whole genome mapping of the binding sites of DNA-associated proteins.
- Whole Genome Sequencing: sequences the whole DNA sequence of an organism’s genome.
- De novo Sequencing: provides the primary genetic sequence of an organism.
- Metagenomic Sequencing: sequencing and identifying the genomes of whole microbial communities.
- Methyl-Seq: analysis of methylation patterns on a genome wide scale.
- Affymetrix 3′ Expression Arrays: target the 3′ end of genes.
- Affymetrix Exon Arrays: provides expression levels for every known exon in the genome.
- Affymetrix miRMA Arrays: provides measurements of small non-coding RNA transcripts involved in gene regulation.
- Affymetrix Genome-Wide Human SNP Array: copy number analysis
- Affymetrix GeneChip Tiling Arrays: gene regulation analysis
Biological Functional and Pathway Analysis: we have software from Ingenuity Systems (IPA) that can analyze your expression data to ascertain the top biological functions and pathways associated with them.
Biological Literature Survey: we have software from Acumenta (Literature Lab) that helps perform data mining tasks on experimentally derived gene lists.
miRNA target prediction: we use in house software and open source software such as TargetScan, miRanda for detecting genomic targets for miRNAs.
Transcription Factor Binding Site Prediction: we use in house software and open source software such as MEME, Homer, PGMotifScan to identify protein DNA interaction sites.