; The overall goal of this core is to centralize data management and analysis services, and thus assure that information produced in the research projects is made available to the scientific community. We will specifically enable assembly of integrated datasets and comparison of results across projects. A secondary goal is to centralize bioinformatics expertise for sequencing analysis. Core C aims to provide and manage a database of blood samples (Aim 1) and provide a central database to characterize and track the enrolled donors and collected samples that will be utilized by all projects. The database will be web-accessible and provide a consistent basis upon which to select samples and interpret results. The database will store general information on the enrolled donors and time dependent clinical information associated with each blood donation, such as presence of symptoms or state of SIT. Laboratory information such as HLA typing data and specific donor &tetramer reactivities will also be stored. Second, we will provide bioinformatic and statistical support to all projects (Aim 2). We will identify the immune response signatures associated with seasonal changes and different disease states (Project 1), and with SIT (Project 2), and the molecular signature associated with asthma (Project 3). Finally, we will assemble, integrate, and submit experimental data to public repositories (Aim3). The research projects in this application will generate large amounts of unique data that will be useful to the scientific community at large. We therefore aim to share our data widely by making them publically available in appropriate repositories.
The data management and analysis services provided by Core C will assure that the Information gained from the research in each project is made accessible and will be comparable across all projects. The high throughput sequencing data analysis services will make specialist bioinformatics expertise available for two of the research projects.
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|Oseroff, Carla; Christensen, Lars H; Westernberg, Luise et al. (2016) Immunoproteomic analysis of house dust mite antigens reveals distinct classes of dominant T cell antigens according to function and serological reactivity. Clin Exp Allergy :|
|Seumois, GrÃ©gory; Zapardiel-Gonzalo, Jose; White, Brandie et al. (2016) Transcriptional Profiling of Th2 Cells Identifies Pathogenic Features Associated with Asthma. J Immunol 197:655-64|
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|Carrasco Pro, Sebastian; Sidney, John; Paul, Sinu et al. (2015) Automatic Generation of Validated Specific Epitope Sets. J Immunol Res 2015:763461|
|Paul, Sinu; Lindestam Arlehamn, Cecilia S; Scriba, Thomas J et al. (2015) Development and validation of a broad scheme for prediction of HLA class II restricted T cell epitopes. J Immunol Methods 422:28-34|
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