BIOINFORMATICS & HIGH-DIMENSIONAL DATA ANALYSIS SHARED RESOURCE ABSTRACT Recent years have seen enormous growth in the complexity and importance of high-dimensional data and the specialized methods and skills required for its successful analysis and integration. To address this emerging need, and to address previous critiques, the Bioinformatics and High-Dimensional Data Analysis Shared Resource (Bioinformatics) was developed by consolidating informatics components that were previously distributed in Biostatistics and three other shared resources, forming a data analysis-focused Resource with broadened scope, enhanced expertise and expanded capabilities. The reorganized Resource provides state-of- the-art informatics and data analysis for genomics, cheminformatics, image analysis and other complex problems. Faculty Director Jeremy Edwards, PhD (CGEG) is a genomics and bioinformatics expert and co- Directors Tudor Oprea, MD,PhD (CT) and Keith Lidke, PhD (TCBS) lead the cheminformatics and image analysis components of the Resource, respectively. The reorganized Resource is now well positioned to promote interdisciplinary research and to develop innovative and significant methodologies in cancer research. The Resource works closely with the other Shared Resources that generate large, complex data sets and with the faculty in the Biostatistics Shared Resource who provide complementary expertise. The Resource Directors collaborate with users to design experiments, develop new methods for data analysis and interpretation, to integrate therapeutic knowledge and to assist with grant writing and data processing for publications. The Resource maintains its own specialized computational resources, appropriate databases and software for accomplishing its diverse goals. It also works closely with UNMCC Research Programs to develop and integrate new methodologies into research projects, and actively facilitates and disseminates information about new approaches and data analysis techniques by maintaining an up-to-date web page, promoting training and education related to high-dimensional data collection and analysis and by giving presentations at UNMCC meetings and retreats. The UNM Cancer Center Research Administration (CCRA) manages the Resource, which operates through a collaborative model. During the previous 5-yr project period, 16 UNMCC members from all 4 Research Programs used the bioinformatics component of the former Biostatistics and Bioinformatics Shared Resource, resulting in a total of 10 publications (2 have pending PMCIDs). In the reporting year of July 2013 ? June 2014, 16 UNMCC members were responsible for 100% of total Resource usage and were supported by 7 peer-reviewed grants. However, another 18 UNMCC members, supported by 14 more grants and responsible for 18 additional peer-reviewed publications, were supported by bioinformatics components in 3 other shared resources, which have now been consolidated. Consequently, the reorganized Bioinformatics and High- Dimensional Data Analysis Shared Resource is projected to have dramatically increased use and importance due to its enhanced capabilities and as more projects develop that involve Big Data.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
3P30CA118100-15S9
Application #
10230654
Study Section
Subcommittee I - Transistion to Independence (NCI)
Program Officer
Ptak, Krzysztof
Project Start
2005-09-26
Project End
2021-08-31
Budget Start
2019-09-01
Budget End
2020-08-31
Support Year
15
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of New Mexico Health Sciences Center
Department
Type
DUNS #
829868723
City
Albuquerque
State
NM
Country
United States
Zip Code
87131
Kumar, Suresh; Jain, Ashish; Farzam, Farzin et al. (2018) Mechanism of Stx17 recruitment to autophagosomes via IRGM and mammalian Atg8 proteins. J Cell Biol 217:997-1013
Vicuña, Belinda; Delaney, Harold D; Flores, Kristina G et al. (2018) Preferences for multigene panel testing for hereditary breast cancer risk among ethnically diverse BRCA-uninformative families. J Community Genet 9:81-92
Feng, Bing; Hoskins, William; Zhang, Yan et al. (2018) Bi-stream CNN Down Syndrome screening model based on genotyping array. BMC Med Genomics 11:105
Phinney, Brandon B; Ray, Anita L; Peretti, Amanda S et al. (2018) MK2 Regulates Macrophage Chemokine Activity and Recruitment to Promote Colon Tumor Growth. Front Immunol 9:1857
Kuehl, Philip J; Grimes, Marcie J; Dubose, Devon et al. (2018) Inhalation delivery of topotecan is superior to intravenous exposure for suppressing lung cancer in a preclinical model. Drug Deliv 25:1127-1136
Köbel, Martin; Luo, Li; Grevers, Xin et al. (2018) Ovarian Carcinoma Histotype: Strengths and Limitations of Integrating Morphology With Immunohistochemical Predictions. Int J Gynecol Pathol :
Bredemeyer, Andrea L; Edwards, Bruce S; Haynes, Mark K et al. (2018) High-Throughput Screening Approach for Identifying Compounds That Inhibit Nonhomologous End Joining. SLAS Discov 23:624-633
Orlow, Irene; Shi, Yang; Kanetsky, Peter A et al. (2018) The interaction between vitamin D receptor polymorphisms and sun exposure around time of diagnosis influences melanoma survival. Pigment Cell Melanoma Res 31:287-296
Sharma, Geetanjali; Mauvais-Jarvis, Franck; Prossnitz, Eric R (2018) Roles of G protein-coupled estrogen receptor GPER in metabolic regulation. J Steroid Biochem Mol Biol 176:31-37
Perez, Dominique R; Edwards, Bruce S; Sklar, Larry A et al. (2018) High-Throughput Flow Cytometry Drug Combination Discovery with Novel Synergy Analysis Software, SynScreen. SLAS Discov 23:751-760

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