Analyzing, managing, and interpreting data accumulated in the age of accessible genomics involves tremendous challenges. A shared resource consisting of informatics and computational scientists, a group of specially trained professionals who understand both biomedical and computer science methodologies, fills the collaboration gap between members, IT professionals, and computational scientists. The overall goal of the Cancer Informatics Core (CIC) is to facilitate the biomedical and translational research of Moffitt Cancer Center (MCC) members through implementation and development of methods and tools to record, integrate, manage, analyze, visualize, and share biomedical, behavioral, and clinical data. To accomplish its goal, the CIC's Specific Aims are to: 1) Support members' 'omics projects with bioinformatics project design, analysis, biological interpretation, and visualizations: The CIC provides bioinformatics and big data analysis and collaborates closely with the Biostatistics Core (BC) to provide seamless analytical services for member projects involving expression profiling, next-generation sequencing, and proteomics. Services include QC, normalization, batch correction, phenotypic analysis, and biological pathway enrichment. 2) Support members' data management and reporting needs with study-specific informatics tools: Complex, study-specific data are collected for member biomedical research studies, including large multi- project studies such as SPOREs. 3) Provide educational opportunities to train members and staff on the use of bioinformatics resources and tools: Public resources are available for members and staff to extract biomedical data and knowledge, leveraging work of the entire scientific community. The CIC provides training for members for awareness of and access to these resources directly. The CIC includes three faculty members, a core facility manager, five staff scientists, and three software developers. CIC bioinformatics faculty devote 50-70% effort to MCC collaborative research activities, supported by CCSG, other grant, and institutional funding. Staff scientists and software developers are dedicated 100% to the CIC, supported by CCSG funding, chargebacks, and institutional support. CIC faculty and staff members are involved in all stages of scientific research, from supporting experimental design (with the Biostatistics Core) to publication of research findings. The CIC has provided significant impact in member research studies through bioinformatics analysis in genomics, proteomics, and expression profiling resulting in high-impact publications in journals such as Nature Genetics and Cancer Research. Over the past five years, the CIC has supported scientific projects of members of all programs, resulting in 62 publications. In the most recent fiscal year, the CIC supported 35 members, with 84% of usage by peer-review-funded members.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA076292-21
Application #
9637345
Study Section
Subcommittee I - Transistion to Independence (NCI)
Project Start
Project End
Budget Start
2019-02-01
Budget End
2020-01-31
Support Year
21
Fiscal Year
2019
Total Cost
Indirect Cost
Name
H. Lee Moffitt Cancer Center & Research Institute
Department
Type
DUNS #
139301956
City
Tampa
State
FL
Country
United States
Zip Code
33612
Cherezov, Dmitry; Hawkins, Samuel H; Goldgof, Dmitry B et al. (2018) Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial. Cancer Med 7:6340-6356
Simmons, Vani N; Sutton, Steven K; Meltzer, Lauren R et al. (2018) Long-term outcomes from a self-help smoking cessation randomized controlled trial. Psychol Addict Behav 32:710-714
Dai, Juncheng; Li, Zhihua; Amos, Christopher I et al. (2018) Systematic analyses of regulatory variants in DNase I hypersensitive sites identified two novel lung cancer susceptibility loci. Carcinogenesis :
Lin, Hui-Yi; Huang, Po-Yu; Chen, Dung-Tsa et al. (2018) AA9int: SNP interaction pattern search using non-hierarchical additive model set. Bioinformatics 34:4141-4150
Neumeyer, Sonja; Banbury, Barbara L; Arndt, Volker et al. (2018) Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer. Br J Cancer 118:1639-1647
Wheldon, Christopher W; Schabath, Matthew B; Hudson, Janella et al. (2018) Culturally Competent Care for Sexual and Gender Minority Patients at National Cancer Institute-Designated Comprehensive Cancer Centers. LGBT Health 5:203-211
Trabert, Britton; Poole, Elizabeth M; White, Emily et al. (2018) Analgesic Use and Ovarian Cancer Risk: An Analysis in the Ovarian Cancer Cohort Consortium. J Natl Cancer Inst :
Palmer, Amanda M; Brandon, Thomas H (2018) How do electronic cigarettes affect cravings to smoke or vape? Parsing the influences of nicotine and expectancies using the balanced-placebo design. J Consult Clin Psychol 86:486-491
Hellmann, Matthew D; Callahan, Margaret K; Awad, Mark M et al. (2018) Tumor Mutational Burden and Efficacy of Nivolumab Monotherapy and in Combination with Ipilimumab in Small-Cell Lung Cancer. Cancer Cell 33:853-861.e4
Wu, Xiaowei; Ji, Haitao (2018) Rhodium(iii)-catalyzed C-H allylation of indoles with allyl alcohols via ?-hydroxide elimination. Org Biomol Chem 16:5691-5698

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