# Structural and Functional Genomics > **NIH NIH P30** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $28,289 ## Abstract STRUCTURAL AND FUNCTIONAL GENOMICS ABSTRACT The goals of the Structural and Functional Genomics Program (SFG) are aligned and integrated with the vision and strategies of Moores Cancer Center (MCC) and the UC San Diego School of Medicine. They use the SFG members’ interdisciplinary strength and expertise in computational biology and genomics to employ a full range of both structural and functional genomic data to elucidate complex signaling pathways and identify candidate targets and compounds that can be translated into novel diagnostic and therapeutic targets and clinical interventions. Approved by the NCI in 1997, the Cancer Genetics Program has evolved to SFG to reflect how, during the past project period, members have expanded use of multi-omic data types, moved analysis methods to molecular tumor boards, and elucidated context-dependent molecular states for more targeted treatments. SFG has 36 members from 14 academic departments with $19.2M of peer-reviewed research grant funding (annual direct costs), $6.3M (33%) of which is from the NCI. SFG members published 714 programmatically aligned articles since 2013, 11% were the result of intra-programmatic collaborations, 20% were inter-programmatic, and 34% were inter-NCI Cancer Center. SFG’s specific aims are to: 1) develop innovative, integrative computational genomic methods that synthesize multi-omic patient and clinical data to drive fundamental and translational cancer research and to disseminate them to the broader cancer research community; 2) analyze genetic, transcriptomic, epigenetic, proteomic, immunologic, and metabolomic data to elucidate the underlying biological pathways and mechanisms of cancer development and progression; and 3) characterize context dependent, functional states of tumor cells and understand the dynamics of resistance in order to identify novel diagnostic, prognostic, and therapeutic strategies, including combination therapies. SFG themes are data science and machine learning, signature and network approaches, and precision therapy. SFG is co-led by Joseph Califano, a head and neck surgeon and translational researcher who applies genomics to develop novel prognostic indicators and therapies and Jill Mesirov, a computational biologist who analyzes complex genome-scale cancer datasets to better understand the underlying mechanisms of cancer, stratify patients, and identify candidate therapies. Their complementary expertise and highly integrated efforts foster collaboration among the outstanding SFG investigators who are leaders in their fields with track records of extraordinary productivity and inter- programmatic collaborations among the MCC research programs. As a result, SFG members have conducted paradigm-shifting studies defining the broad role of extrachromosomal DNA in human cancers, developed carcinogen-based mutational signatures across cancer types, demonstrated the role of the microbiome in hepatocellular cancer development, and produced and maintain... ## Key facts - **NIH application ID:** 10160802 - **Project number:** 5P30CA023100-35 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO - **Principal Investigator:** Joseph A Califano - **Activity code:** P30 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $28,289 - **Award type:** 5 - **Project period:** 1996-07-01 → 2024-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10160802 ## Citation > US National Institutes of Health, RePORTER application 10160802, Structural and Functional Genomics (5P30CA023100-35). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10160802. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*