# Core C: Data Management and Biostatistics > **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $222,727 ## Abstract ABSTRACT This Data Management and Biostatistics Core (DBC) is designed to provide high-quality data management infrastructure and statistical support, while using innovation and creativity to improve the delivery of our core functions to investigators. The overarching goal for the PPG is to integrate basic science and clinical resources to investigate the clinical, imaging, molecular, and neuropathological features of FTD. Historically, this PPG has used sophisticated approaches to phenotyping patients, linking clinical signs and symptoms back to neuroanatomic, genetic, and proteomic signatures to improve early and accurate diagnosis of FTD. Thus, the DMB Core for this PPG has a particular mandate to support and facilitate our researchers' ability to link the complex, multilevel data we collect, and to approach that data with appropriately sophisticated recommendations for research design and analytic methods. At the center of the PPG is a comprehensive database built using the LAVA platform, a data management solution specifically designed at UCSF for use by integrative clinical research centers. It provides support for administrative, clinical and research procedures for central cores and affiliated projects that share common patient cohorts and assessment protocols. Since the last renewal of this PPG, we have also developed a suite of browser-based tools designed to work with MAC data and help solve the problems posed by the complex, multidimensional data generated across PPG projects and cores. This platform, called the KNECT system (Knowledge Network Core Technology), comprises both single-patient data integration and normative interpretation across clinical, imaging, and genetic modalities, and rapid data linking, analysis, and visualization of aggregate patient data, with tools for combining phenotypic and genetic data with structural and resting-state functional MRI data. Finally, this core is designed to provide integrated research design and biostatistical consultation to PPG personnel, guiding researchers to approach similar problems in a consistent manner across projects and cores using the highest quality and most reliable statistical approaches. Thus, the aims of this core are: AIM 1: To develop and maintain centralized, integrated data management systems and procedures that ensure the accuracy, availability, and confidentiality of administrative, clinical, and research data from PPG cores and projects. AIM 2: To provide PPG researchers with data integration and analysis tools supporting their ability to effectively combine and utilize data across cores and projects to accelerate discovery. AIM 3: To provide high-quality biostatistical consultation to all PPG cores and projects in order to systematically unify and focus research design and statistical analysis. AIM 4: To promote research methods integration and collaboration among PPG cores, projects, and related research protocols through efficient data sharing, coordinated data an... ## Key facts - **NIH application ID:** 9949602 - **Project number:** 5P01AG019724-19 - **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO - **Principal Investigator:** Katherine P Rankin - **Activity code:** P01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $222,727 - **Award type:** 5 - **Project period:** — → — ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/9949602 ## Citation > US National Institutes of Health, RePORTER application 9949602, Core C: Data Management and Biostatistics (5P01AG019724-19). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9949602. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*