Computational Core: Biostatistical Analysis and Network Modelling

NIH RePORTER · NIH · P01 · $213,651 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY This application proposes three research Projects and three Cores for shared resources initiated and led by investigators at the University of California Los Angeles (UCLA), centered around the theme of investigating innate-adaptive immunoregulation in liver transplant ischemia/reperfusion Injury (IRI). Projects 1 and 2 focus on IRI meditation of immune responses following hepatic grafting in syngeneic and allogeneic murine models, respectively; whereas, Project 3 concentrates on elucidating the role of IRI on immunoregulation following human OLT. The Computational Core provides data management, biostatistical and computational expertise required for the proper analysis and network modelling of data generated by Projects. Modelling will allow the integration of findings from the three types of liver transplants. Services will be provided in the following areas:  Data monitoring and management.  A central infrastructure for data preprocessing of high throughput molecular data.  Biostatistical design, analysis and interpretation of project studies.  Statistical monitoring of studies to ensure interpretability of results.  Development of biostatistical methodology for statistical problems in these projects.  Modeling the immune-cell dynamics to interpret immune-phenotyping datasets.  Process digital histopathology images using a deep learning approach called generative adversarial networks (GAN) to aid in computational/digital quantification and prediction of expressed proteins and spatially resolved genes at pathologic features of interest.  Integrate molecular and cellular scale data and analyses using matrix factorization and tensor decomposition.  Assistance with manuscript preparation.

Key facts

NIH application ID
10328212
Project number
2P01AI120944-06
Recipient
UNIVERSITY OF CALIFORNIA LOS ANGELES
Principal Investigator
David Gjertson
Activity code
P01
Funding institute
NIH
Fiscal year
2022
Award amount
$213,651
Award type
2
Project period
2017-08-01 → 2027-07-31