Data Science Core Overview

The Data Science Core (DSC) has assembled teams of data scientists, biostatisticians, and computer specialists to 1) work with biomedical researchers in designing experiments, analyzing data, and interpreting results that lead to publications and grant applications; 2) collaborate with existing data science resources in Kansas to provide access to the cyberinfrastructure required to transfer, store, analyze, and interpret large data sets; 3) develop pipelines and databases that foster collaboration, and multidisciplinary science, 4) provide training opportunities in the form of workshops, seminars, and student research scholarships that will facilitate the practical application of these resources by K-INBRE trainees and faculty; and 5) develop course curricula to train the next generation of biomedical researchers in data science. Overall, the DSC has had excellent progress and is proactive in increasing data science scholars in Kansas.

Inquires

The K-INBRE Data Science Core is committed to collaborating with Kansas researchers to perform cutting edge research in biomedical research. We also provide semi-annual training workshops to introduce scientists to computational tools and NGS pipelines. If you have any questions regarding  collaboration opportunities, services provided by the Core or scheduled workshops please contact any of the specialists or directors listed below.

Kansas State University (KSU)

The K-INBRE Data Science Core is led by Dr. Bradley Olson, Associate Professor in Biology. Dr. Olson is an expert in data science, artificial intelligence, multi-omics, genome sequencing, mapping and informatics. Data science specialists at the KSU Core focus on data analytics, multi-omics integration, genome and transcriptome assembly, gene annotation, RNA-Seq analysis, and taxon identification from metagenomics samples. Members of the KSU core also serve as liaisons between data science satellite cores at KUMC and KU-L, faculty members at Kansas’ primarily undergraduate institutions (PUIs), and the other branches of the K-INBRE network.

University of Kansas Medical Center (KUMC)

The KUMC satellite core is led by Devin Koestler, Professor in the Department of Biostatistics & Data Science at the University of Kansas Medical Center. Dr. Koestler’s specialty is statistical genomics. He focuses on the development and application of novel bioinformatics/statistical methodologies for identifying biologically and clinically relevant patterns in high-throughput ‘omic data, with an emphasis on computationally efficient clustering methodologies for identifying molecular subtypes of human diseases. Bioinformatics specialists at the KUMC Core have extensive experience in the design and analysis of ‘omic studies using both microarray and high-throughput sequencing technologies and provide the core with expertise in statistical analysis and clinical studies.

University of Kansas (KU-L)

The satellite DSC at KU-Lawrence is led by Dr. Stuart Macdonald, Professor, Molecular Biosciences. Dr. Macdonald’s research interest is in understanding the molecular genetic basis of complex traits, and his group uses an array of genomic and analytical tools to accomplish this. The KU DSC is staffed by a full-time genomic data scientist, Dr. Brian Sanderson (see below), who has an array of experience with the computational analysis of genomics data. Our website describes our facility and services. We are able to assist with a range of data analysis problems, including (but not limited to):

• Using RNA-sequencing to understand changes in gene expression among individuals, tissues, and treatments.
• Understanding the relationship between genetic and phenotypic variation.
• Finding variants in whole-genome re-sequencing data.

We are available to assist in the design of rigorous/powerful genomics experiments. We will implement efficient, reproducible workflows for analyzing genomics data. We can generate publication-ready figures, and other products necessary for publications and grant proposals. And we can provide education and training in the analysis of next-generating sequencing data (e.g., from whole genome sequencing, RNAseq, etc) to answer biological questions.

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Data Science Core Contacts

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KANSAS STATE UNIVERSITY

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UNIVERSITY OF KANSAS

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UNIVERSITY OF KANSAS MEDICAL CENTER

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