The overall goal of the Bioinformatics Core is to use advanced bioinformatics tools for identification and improved understanding of the innate and adaptive immune response in influenza infection and vaccination and compare with other diseases. The Bioinformatics Core will utilize existing informatics platforms, and adapt them as needed, to achieve these goals. The goals of the Bioinformatics Core will (1) provide robust bioinformatics methods to analyze the data generated by Projects 1, 2 and 3, and (2) analyze data from public repositories including the NIAID-funded ImmPort and the NCBI Gene Expression Omnibus for the Projects for hypothesis testing. The Bioinformatics Core will directly work with all Projects to address their need for robust bioinformatics techniques. The Bioinformatics Core will integrate the immune profiling data generated by all Projects with those available from public repositories, to enable multi-cohort integrated analysis. The Bioinformatics Core will work closely with the Human Immune Monitoring Center (HIMC) for this purpose. This will enable participating Projects to maximally utilize the genomic, immune monitoring and clinical phenotypic data sets to determine functional dependencies among the measured elements and to direct further biological validation of these putative dependencies.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
2U19AI057229-16
Application #
9674971
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
16
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Sweeney, Timothy E; Thomas, Neal J; Howrylak, Judie A et al. (2018) Multicohort Analysis of Whole-Blood Gene Expression Data Does Not Form a Robust Diagnostic for Acute Respiratory Distress Syndrome. Crit Care Med 46:244-251
Kronstad, Lisa M; Seiler, Christof; Vergara, Rosemary et al. (2018) Differential Induction of IFN-? and Modulation of CD112 and CD54 Expression Govern the Magnitude of NK Cell IFN-? Response to Influenza A Viruses. J Immunol 201:2117-2131
Wilk, Aaron J; Blish, Catherine A (2018) Diversification of human NK cells: Lessons from deep profiling. J Leukoc Biol 103:629-641
Sweeney, Timothy E; Wynn, James L; Cernada, María et al. (2018) Validation of the Sepsis MetaScore for Diagnosis of Neonatal Sepsis. J Pediatric Infect Dis Soc 7:129-135
Bukhari, Syed Ahmad Chan; O'Connor, Martin J; Martínez-Romero, Marcos et al. (2018) The CAIRR Pipeline for Submitting Standards-Compliant B and T Cell Receptor Repertoire Sequencing Studies to the National Center for Biotechnology Information Repositories. Front Immunol 9:1877
Azad, Tej D; Donato, Michele; Heylen, Line et al. (2018) Inflammatory macrophage-associated 3-gene signature predicts subclinical allograft injury and graft survival. JCI Insight 3:
Leipold, Michael D; Obermoser, Gerlinde; Fenwick, Craig et al. (2018) Comparison of CyTOF assays across sites: Results of a six-center pilot study. J Immunol Methods 453:37-43
Sibener, Leah V; Fernandes, Ricardo A; Kolawole, Elizabeth M et al. (2018) Isolation of a Structural Mechanism for Uncoupling T Cell Receptor Signaling from Peptide-MHC Binding. Cell 174:672-687.e27
Ju, Chia-Hsin; Blum, Lisa K; Kongpachith, Sarah et al. (2018) Plasmablast antibody repertoires in elderly influenza vaccine responders exhibit restricted diversity but increased breadth of binding across influenza strains. Clin Immunol 193:70-79
Sweeney, Timothy E; Perumal, Thanneer M; Henao, Ricardo et al. (2018) A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun 9:694

Showing the most recent 10 out of 249 publications