Abstract

The Markey Cancer Center (MCC) Cancer Research Informatics (CRI) Shared Resource Facility facilitates collaborative research among members of the MCC through the optimal application of informatics technologies and methods that maximize the accessibility and usability of data, information, and knowledge for cancer research. The primary goal of CRI is to provide comprehensive and centralized data acquisition and informatics support that is readily available to cancer center members.
The Specific Aims of the CRI are to: 1. Develop and support innovative technologies for funded research studies that facilitate accurate, timely, and secure data acquisition and dissemination. 2. Maintain and support a comprehensive patient-centered data warehouse offering unique opportunities for MCC investigators to utilize integrated data sets from diverse sources ranging from genetic biomarkers to population-based surveillance data. 3. Facilitate rapid and efficient recruitment of patients to investigator-initiated trials and other research studies. 4. Facilitate investigator access to data, biospecimens, and patients from Kentucky's Appalachian population. 5. Ensure the interoperability of informatics systems in compliance with evolving data standards. 6. Collaborate with the University of Kentucky (UK) Division of Biomedical Informatics to provide novel and state-of-the-art informatics solutions that increase the efficiency and accuracy of information and knowledge derived from diverse data sources.

Public Health Relevance

The CRI is a critical resource supporting the acquisition, storage, management and utilization of data, information, and knowledge. The CRI integrates data from population, clinical, and research sources to identify and recruit study participants, annotate biospecimens, and derive unique research datasets for MCC investigators. This shared resource provides value-added service to MCC members, which has led to numerous publications and research grants from the NCI and other funding agencies.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA177558-05
Application #
9304073
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
5
Fiscal Year
2017
Total Cost
Indirect Cost

  Institution

Name
University of Kentucky
Department
Type
DUNS #
939017877
City
Lexington
State
KY
Country
United States
Zip Code
40526

  Publications

Banerjee, Moumita; Cui, Xiaoyu; Li, Zhichuan et al. (2018) Na/K-ATPase Y260 Phosphorylation-mediated Src Regulation in Control of Aerobic Glycolysis and Tumor Growth. Sci Rep 8:12322
Ji, Xuemei; Bossé, Yohan; Landi, Maria Teresa et al. (2018) Identification of susceptibility pathways for the role of chromosome 15q25.1 in modifying lung cancer risk. Nat Commun 9:3221
McKenna, Mary K; Noothi, Sunil K; Alhakeem, Sara S et al. (2018) Novel role of prostate apoptosis response-4 tumor suppressor in B-cell chronic lymphocytic leukemia. Blood 131:2943-2954
Jones, Derek; Bopaiah, Jeevith; Alghamedy, Fatemah et al. (2018) Polypharmacology Within the Full Kinome: a Machine Learning Approach. AMIA Jt Summits Transl Sci Proc 2017:98-107
Crooks, Daniel R; Maio, Nunziata; Lane, Andrew N et al. (2018) Acute loss of iron-sulfur clusters results in metabolic reprogramming and generation of lipid droplets in mammalian cells. J Biol Chem 293:8297-8311
Zhang, Yi; Liu, Xinan; MacLeod, James et al. (2018) Discerning novel splice junctions derived from RNA-seq alignment: a deep learning approach. BMC Genomics 19:971
Liu, Jinpeng; Murali, Thilakam; Yu, Tianxin et al. (2018) Characterization of Squamous Cell Lung Cancers from Appalachian Kentucky. Cancer Epidemiol Biomarkers Prev :
Ore, Robert M; Chen, Quan; DeSimone, Christopher P et al. (2018) Population-Based Analysis of Patient Age and Other Disparities in the Treatment of Ovarian Cancer in Central Appalachia and Kentucky. South Med J 111:333-341
Hubbard, W Brad; Harwood, Christopher L; Geisler, John G et al. (2018) Mitochondrial uncoupling prodrug improves tissue sparing, cognitive outcome, and mitochondrial bioenergetics after traumatic brain injury in male mice. J Neurosci Res 96:1677-1688
Alghamedy, Fatemah; Bopaiah, Jeevith; Jones, Derek et al. (2018) Incorporating Protein Dynamics Through Ensemble Docking in Machine Learning Models to Predict Drug Binding. AMIA Jt Summits Transl Sci Proc 2017:26-34

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