The Bioinformatics Core C will establish and support Program-wide computing resources for automated data processing, access to specialized tools and resources, Program data integration, collaborative support within and among Cores and Projects and integrated data distribution and educational activities for all components of the Program Project.
Specific aims are: 1) continue to develop and deploy an integrated infrastructure to support day to day activities of the Projects and other Cores by evaluating common and Project specific requirements, coordinating, integrating, deploying and maintaining all shared bioinformatic and computing resources including hardware, software, software engineering, security, training, and related quality assurance programs;2) to develop novel bioinformatic resources where no existing tools or resources are applicable for a specific requirement, by analyzing, specifying, developing, testing, deploying and supporting novel software, methods, infrastructure, resources and tools to meet the specific needs of each of the Projects and other Cores;3) develop and deploy collaboration, education and dissemination resources for both internal and external partners by developing and maintaining modern internet based collaborative support tools and resources, training, data transfer and data transformation services for internal use by Program participants, and tools, educational programs and resources for external and public partners including secured external data and information access together with related training and support activities. BIDS infrastructure will integrate and support experimental, genotype and phenotype data management, data aggregation, data consistency and validation, data security, data transformation, data archiving, and internal data and information sharing between all Projects and Cores, and will also establish and maintain a coherent public, internet accessible interface for disseminating data, and other resources from the entire Program to the wider community.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Program Projects (P01)
Project #
5P01HL083069-05
Application #
8209733
Study Section
Heart, Lung, and Blood Initial Review Group (HLBP)
Project Start
Project End
2014-01-31
Budget Start
2011-02-01
Budget End
2013-01-31
Support Year
5
Fiscal Year
2011
Total Cost
$267,271
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
McGeachie, Michael J (2017) Childhood asthma is a risk factor for the development of chronic obstructive pulmonary disease. Curr Opin Allergy Clin Immunol 17:104-109
Hobbs, Brian D; Parker, Margaret M; Chen, Han et al. (2016) Exome Array Analysis Identifies a Common Variant in IL27 Associated with Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 194:48-57
Hardin, M; Cho, M H; McDonald, M-L et al. (2016) A genome-wide analysis of the response to inhaled ?2-agonists in chronic obstructive pulmonary disease. Pharmacogenomics J 16:326-35
Kitsak, Maksim; Sharma, Amitabh; Menche, Jörg et al. (2016) Tissue Specificity of Human Disease Module. Sci Rep 6:35241
Ierodiakonou, Despo; Zanobetti, Antonella; Coull, Brent A et al. (2016) Ambient air pollution, lung function, and airway responsiveness in asthmatic children. J Allergy Clin Immunol 137:390-9
Howrylak, Judie A; Moll, Matthew; Weiss, Scott T et al. (2016) Gene expression profiling of asthma phenotypes demonstrates molecular signatures of atopy and asthma control. J Allergy Clin Immunol 137:1390-1397.e6
McGeachie, M J; Yates, K P; Zhou, X et al. (2016) Patterns of Growth and Decline in Lung Function in Persistent Childhood Asthma. N Engl J Med 374:1842-1852
McGeachie, Michael J; Yates, Katherine P; Zhou, Xiaobo et al. (2016) Genetics and Genomics of Longitudinal Lung Function Patterns in Individuals with Asthma. Am J Respir Crit Care Med 194:1465-1474
Zhou, Jin J; Cho, Michael H; Lange, Christoph et al. (2015) Integrating Multiple Correlated Phenotypes for Genetic Association Analysis by Maximizing Heritability. Hum Hered 79:93-104
Sharma, Amitabh; Menche, Jörg; Huang, C Chris et al. (2015) A disease module in the interactome explains disease heterogeneity, drug response and captures novel pathways and genes in asthma. Hum Mol Genet 24:3005-20

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