GENOMICS AND COMPUTATIONAL BIOLOGY SHARED RESOURCE ABSTRACT The Genomics and Computational Biology Shared Resource (GCBSR) is directed by KA Frazer, an established and highly productive investigator, who has broad expertise in the field of genomics, and co- directed by P Tamayo, a well-funded experienced computational biologist and cancer genomics researcher. Together, they oversee a confederation of 2 units that make up the GCBSR: Institute for Genomic Medicine Genomics Center (IGM Genomics Center), operationally directed by Kristen Jepsen, and the Center for Computational Biology and Bioinformatics (CCBB), operationally directed by Kathleen Fisch. The GCBSR consists of an integrated team of highly qualified scientists, engineers and technicians with the requisite expertise in study design, data generation, data analysis and interpretation to enable Moores Cancer Center (MCC) investigators to execute high-throughput genomics projects. The major objectives of the GCBSR are to provide MCC investigators with high quality, cutting edge genomic profiling and data analysis services, as well as with consultation on experimental design and training/education. This will enable MCC researchers to conduct innovative research on high priority projects central to the goals of the MCC strategic plan and the Research Programs. The overarching goals of the GCBSR are to: 1) Provide expert consultation to MCC membership on experimental designs and analysis approaches of large-scale genomics datasets; 2) Generate high-throughput sequence data in a cost-effective manner and offer this as a service for the MCC membership; 3) Perform primary analysis and interpretation of high-throughput sequence data including, DNA variant calling, mRNA isoform calling, miRNA analysis and DNA methylation analysis; and 4) Perform advanced integrative data analysis including, tumor profiling for DNA somatic mutations, differential expression analysis, gene enrichment analysis, network and systems analysis. Previously rated Outstanding, several improvements were made during the project period to ensure that the GCBSR continues to keep pace with current technologies and continues to provide the highest quality cost-effective services to MCC members. The GCBSR acquired several cutting-edge pieces of equipment that have increased throughput, lowered prices, and provided newly available technologies to MCC users. Furthermore, GCBSR created a bioinformatics and computational biology resource to support the analysis of large molecular datasets, with special emphasis in the areas of genomics, transcriptomics, systems biology, cancer genomics and translational medicine.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Center Core Grants (P30)
Project #
5P30CA023100-34
Application #
9936325
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
34
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Dow, Michelle; Pyke, Rachel M; Tsui, Brian Y et al. (2018) Integrative genomic analysis of mouse and human hepatocellular carcinoma. Proc Natl Acad Sci U S A 115:E9879-E9888
Que, Xuchu; Hung, Ming-Yow; Yeang, Calvin et al. (2018) Oxidized phospholipids are proinflammatory and proatherogenic in hypercholesterolaemic mice. Nature 558:301-306
Murzin, Vyacheslav L; Woods, Kaley; Moiseenko, Vitali et al. (2018) 4? plan optimization for cortical-sparing brain radiotherapy. Radiother Oncol 127:128-135
Norton, Jeffrey A; Kim, Teresa; Kim, Joseph et al. (2018) SSAT State-of-the-Art Conference: Current Surgical Management of Gastric Tumors. J Gastrointest Surg 22:32-42
Ikeda, Sadakatsu; Tsigelny, Igor F; Skjevik, Åge A et al. (2018) Next-Generation Sequencing of Circulating Tumor DNA Reveals Frequent Alterations in Advanced Hepatocellular Carcinoma. Oncologist 23:586-593
Buckley, Alexandra R; Ideker, Trey; Carter, Hannah et al. (2018) Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas. Genome Med 10:69
Parish, Austin J; Nguyen, Vi; Goodman, Aaron M et al. (2018) GNAS, GNAQ, and GNA11 alterations in patients with diverse cancers. Cancer 124:4080-4089
Xu, Selene; Thompson, Wesley; Ancoli-Israel, Sonia et al. (2018) Cognition, quality-of-life, and symptom clusters in breast cancer: Using Bayesian networks to elucidate complex relationships. Psychooncology 27:802-809
Tao, Li; Schwab, Richard B; San Miguel, Yazmin et al. (2018) Breast Cancer Mortality in Older and Younger Breast Cancer Patients in California. Cancer Epidemiol Biomarkers Prev :
Sagredo, Eduardo A; Blanco, Alejandro; Sagredo, Alfredo I et al. (2018) ADAR1-mediated RNA-editing of 3'UTRs in breast cancer. Biol Res 51:36

Showing the most recent 10 out of 862 publications