The Biostatistics and Biolnformatics Shared Resource (BBSR) provides biostatistical and bioinformatics leadership and support for research within the Cancer Center. The BBSR plays a critical role in the design and analysis of cancer related investigations, including clinical trials, epidemiological studies, and laboratory-based studies. The BBSR provides a full range of biostatistical services, including study design, sample size calculations, data analysis and interpretation, protocol reviews, and development of novel statistical methodologies. The BBSR also provides support for cancer researchers to store, access, and analyze large-scale genomic, proteomic, clinical, image-based, and systems biology datasets.The overall goals of the Resource are to provide: (1) biostatistical and bioinformatics support to Cancer Center researchers through service and collaborative activities;(2) training in the use of statistical software and biostatistical methods, through regular short courses and one-on-one sessions, and technical guidance and technology background to Cancer Center members and associated scientists seeking to use parallel supercomputing and database hardware and software in cancer-based biomedical research;(3) development of novel biostatistical and bioinformatic methods to enhance Cancer Center research projects; and (4) dissemination of capabilities, by continuing with the development of our website that identifies personnel and services provided to allow wider knowledge of the biostatistical and bioinformatics support available to Cancer Center investigators. Edward J. Bedrick, Ph.D. is Director of the Resource. Susan R. Atlas, Ph.D, and Christine Stidley, Ph.D. are Co-Directors of the Resource for bioinformatics and biostatistics, resectively. Dr. Bedrick has >20 years experience in biostatistics. Dr. Atlas has >20 years experience in scientific computing and bioinformatics. Dr. Stidley supports the large lung cancer research and SEER efforts. The Resource includes eight faculty and scientific staff, with a broad range of areas of expertise. Since 2005, Cancer Center members published more than 40 articles in collaboration with Resource faculty and staff. Resource members are co-investigators on 11 peer-reviewed extra-mural grants with Cancer Center members with several pending. More than 30 Cancer Center members representing all 4 Research Programs are making extensive use ofthe Resource.

Public Health Relevance

The Resource enhances the clinical trials and Research Programs of the Cancer Center by providing critical expertise in the design and analysis of cancer related studies. These research efforts would be not Just hampered, but often rendered meaningless, without appropriate biostatistical and bioinformatics support. The Resource also provides statistical support during the development of projects that will ultimately lead to both increased research funding to the Cancer Center and support for members of the Resource. Furthermore, the Bioinformatics technical staff members provide the mechanisms by which large-scale datasets and associated clinical covariate data generated by Cancer Center researchers are reliably managed, stored, annotated, archived, and disseminated. These activifies are critical to meeting the Specific Aims of Cancer Center research grants that are based on the generation and analysis of large-scale genomic datasets for large patient cohorts and emerging large-scale deep sequencing data.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
3P30CA118100-09S2
Application #
8723113
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
9
Fiscal Year
2013
Total Cost
$6,251
Indirect Cost
$2,111
Name
University of New Mexico Health Sciences Center
Department
Type
DUNS #
829868723
City
Albuquerque
State
NM
Country
United States
Zip Code
87131
Steffen, Laurie E; Du, Ruofei; Gammon, Amanda et al. (2017) Genetic Testing in a Population-Based Sample of Breast and Ovarian Cancer Survivors from the REACH Randomized Trial: Cost Barriers and Moderators of Counseling Mode. Cancer Epidemiol Biomarkers Prev 26:1772-1780
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Leng, Shuguang; Wu, Guodong; Klinge, Donna M et al. (2017) Gene methylation biomarkers in sputum as a classifier for lung cancer risk. Oncotarget 8:63978-63985
Kimura, Tomonori; Jia, Jingyue; Kumar, Suresh et al. (2017) Dedicated SNAREs and specialized TRIM cargo receptors mediate secretory autophagy. EMBO J 36:42-60

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