The aim of the Translational Informatics (Tl) core is to provide the Informatics infrastructure, and to develop, deploy and maintain data systems and applications that optimize the translation of basic scientific discoveries into clinical applications. Tl members are made up of experienced informaticians and clinical research support specialists and analysts with backgrounds in clinical data coordination, biomedical research, molecular biology, computer science, software engineering, and application architecture. The Tl core develops data systems that span a range of users, from individual investigators, to individual programs within the Cancer Center, and to the Cancer Center as a whole. Tl works with researchers, other Cores, and Cancer Center administration to fulfill its goals with the ability to provide customizable informatics solutions for all data needs. Over the next five years, Tl will continue to provide the Cancer Center members with Informatics and computational support for an array of activities, including continued participation in grant applications and expanding efforts as needed to respond to changing needs of funded grants. Tl priorities are to: 1) Access, training, and management of Clinical and Biomedical Software Tools 2) Provide access to Clinical and Biomedical Data for Research 3) Research Data Management Solutions including access to High Performance Compute Cluster and allocated software. Pathway analysis tools (IPA), and design of Data Collection Models 4) Biospecimen Data Management 5) Custom Research Software Development including user interfaces 6) Oversee and provide guidance for Research Data Privacy, Security, and Quality Control 7) Standardize and Harmonize Data Collection Vocabularies and Common Data Elements 8) Maintenance of databases. Patient centric data-warehouse, and associated web sites 9) Custom data services involving specific programming expertise for specialized databases

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA082103-16
Application #
8693945
Study Section
Subcommittee G - Education (NCI)
Project Start
Project End
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
16
Fiscal Year
2014
Total Cost
$650,592
Indirect Cost
$238,620
Name
University of California San Francisco
Department
Type
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Autry, Adam; Phillips, Joanna J; Maleschlijski, Stojan et al. (2017) Characterization of Metabolic, Diffusion, and Perfusion Properties in GBM: Contrast-Enhancing versus Non-Enhancing Tumor. Transl Oncol 10:895-903
Pekmezci, Melike; Rice, Terri; Molinaro, Annette M et al. (2017) Adult infiltrating gliomas with WHO 2016 integrated diagnosis: additional prognostic roles of ATRX and TERT. Acta Neuropathol 133:1001-1016
Maertens, Ophélia; McCurrach, Mila E; Braun, Benjamin S et al. (2017) A Collaborative Model for Accelerating the Discovery and Translation of Cancer Therapies. Cancer Res 77:5706-5711
de Smith, Adam J; Kaur, Maneet; Gonseth, Semira et al. (2017) Correlates of Prenatal and Early-Life Tobacco Smoke Exposure and Frequency of Common Gene Deletions in Childhood Acute Lymphoblastic Leukemia. Cancer Res 77:1674-1683
Stieglitz, Elliot; Mazor, Tali; Olshen, Adam B et al. (2017) Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia. Nat Commun 8:2127
Bartlett, Thomas E; Müller, Sören; Diaz, Aaron (2017) Single-cell Co-expression Subnetwork Analysis. Sci Rep 7:15066
Martin, Thomas; Baz, Rachid; Benson, Don M et al. (2017) A phase 1b study of isatuximab plus lenalidomide and dexamethasone for relapsed/refractory multiple myeloma. Blood 129:3294-3303
Zhang, Jie; Yao, Tsun-Wen; Hashizume, Rintaro et al. (2017) Combined BRAFV600E and MEK blockade for BRAFV600E-mutant gliomas. J Neurooncol 131:495-505
Li, Megan; Kroetz, Deanna L (2017) Bevacizumab-induced hypertension: Clinical presentation and molecular understanding. Pharmacol Ther :
Aggarwal, Rahul; Behr, Spencer C; Paris, Pamela L et al. (2017) Real-Time Transferrin-Based PET Detects MYC-Positive Prostate Cancer. Mol Cancer Res 15:1221-1229

Showing the most recent 10 out of 168 publications