The mission of the Bioinformatics Shared Resource (BISR) is to guarantee the availability of comprehensive bioinformatics expertise to Sidney Kimmel Comprehensive Cancer Center (SKCCC) members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR achieves this by partially funding the effort for several PhD-level investigators and related staff. BISR faculty have extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems. A critical development during the next funding period will be the emergence of large data sets comprising multiple omics data, including genomics (SNPs, allelic variation maps from high-throughput sequencing), epigenomics (methylation an-ays, bi-sulfite high-throughput sequencing), transcriptomics (microarrays and RNA-seq), proteomics (MS-MS and arrays), and metabolomics (MS and NMR). These data will require integration through annotations, both through genome sequence and using proteomic-based integration. Computational modeling of this data will play an increasingly important role, as the data could overwhelm mathematical analysis approaches that lack a biologically motivated model to place the data in context Pathway, network, and cellular systems analysis is expected to play a growing role in data interpretation, with systems biology and computational modeling emerging as critical capabilities for the BISR. This Core has been assembled with the breadth in expertise necessary for these developments. Lay: The Bioinformatics Resource provides comprehensive bioinformatics expertise to Cancer Center members involved in molecular cancer research, with special emphasis on techniques that generate high dimensional data. The BISR has several PhD-level investigators with extensive experience in all aspects of high-throughput biological data analysis and computational modeling of biological systems, together with support staff.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA006973-51
Application #
8661018
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2014-05-01
Budget End
2015-04-30
Support Year
51
Fiscal Year
2014
Total Cost
$295,552
Indirect Cost
$113,483
Name
Johns Hopkins University
Department
Type
DUNS #
001910777
City
Baltimore
State
MD
Country
United States
Zip Code
21218
Zeidner, Joshua F; Zahurak, Marianna; Rosner, Gary L et al. (2015) The evolution of treatment strategies for patients with chronic myeloid leukemia relapsing after allogeneic bone marrow transplant: can tyrosine kinase inhibitors replace donor lymphocyte infusions? Leuk Lymphoma 56:128-34
Penet, Marie-France; Shah, Tariq; Bharti, Santosh et al. (2015) Metabolic imaging of pancreatic ductal adenocarcinoma detects altered choline metabolism. Clin Cancer Res 21:386-95
Sharabi, Andrew B; Nirschl, Christopher J; Kochel, Christina M et al. (2015) Stereotactic Radiation Therapy Augments Antigen-Specific PD-1-Mediated Antitumor Immune Responses via Cross-Presentation of Tumor Antigen. Cancer Immunol Res 3:345-55
Peltonen, Karita; Colis, Laureen; Liu, Hester et al. (2014) A targeting modality for destruction of RNA polymerase I that possesses anticancer activity. Cancer Cell 25:77-90
DeZern, Amy E; Guinan, Eva C (2014) Aplastic anemia in adolescents and young adults. Acta Haematol 132:331-9
Paller, Channing J; Wissing, Michel D; Mendonca, Janet et al. (2014) Combining the pan-aurora kinase inhibitor AMG 900 with histone deacetylase inhibitors enhances antitumor activity in prostate cancer. Cancer Med 3:1322-35
Maldonado, Leonel; Teague, Jessica E; Morrow, Matthew P et al. (2014) Intramuscular therapeutic vaccination targeting HPV16 induces T cell responses that localize in mucosal lesions. Sci Transl Med 6:221ra13
Schweizer, Michael T; Antonarakis, Emmanuel S (2014) Chemotherapy and its evolving role in the management of advanced prostate cancer. Asian J Androl 16:334-40
Huang, Peng; Ou, Ai-hua; Piantadosi, Steven et al. (2014) Formulating appropriate statistical hypotheses for treatment comparison in clinical trial design and analysis. Contemp Clin Trials 39:294-302
Bhatnagar, Akrita; Wang, Yuchuan; Mease, Ronnie C et al. (2014) AEG-1 promoter-mediated imaging of prostate cancer. Cancer Res 74:5772-81

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