The data management approach of the CCNMD is a two tiered plan. Tier one, is to continue to implement a data warehouse system that has recently been developed within the Department of Psychiatry center-wide. Implementation of this system is in progress and provides access to the contributing projects within the CCNMD system integrated data storage and data query capacity immediately. All of the data tables generated by the Brain Bank Core and the Clinical Core during the past 18 years have been integrated into this browser based data warehouse. These data sets are available for interrogation and mining to all CCNMD participants through a secure intranet. Tier two, involves the upgrading of the currently implemented solution to a much more robust and universal data warehouse system with the help of IBM's """"""""Computational Biology Center, Exploratory Server Systems"""""""" that can serve a broader need and set of projects with greater sophistication, security, and universality complying with all existing standards for data security and medical data informatics. Tier one implementation will help ongoing data acquisition and data processing and tier two implementation will achieve unparalleled data integration, security, and data mining capabilities. All of the CCNMD projects will also require considerable statistical data analysis, and because of the complexity of some of the hypotheses addressed a high level of statistical analytic sophistication. While all of the CCNMD investigators are well versed in the statistical approaches that are applicable to their specific hypotheses and projects, this core will provide them with statistical expertise for not only state-of-the-art analysis of their specific data sets, but also for the integration of each projects data with the data derived from the other projects. The integration of cross-project data for statistical analysis will not only be aided by the data management system described, but also by the fact that statistical testing of hypotheses has been an integral part of the development of the aims and hypotheses of each CCNMD project form the time of their inception.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Specialized Center (P50)
Project #
1P50MH066392-01
Application #
6697231
Study Section
Special Emphasis Panel (ZMH1)
Project Start
2002-09-30
Project End
2006-07-31
Budget Start
Budget End
Support Year
1
Fiscal Year
2002
Total Cost
Indirect Cost
Name
Mount Sinai School of Medicine
Department
Type
DUNS #
114400633
City
New York
State
NY
Country
United States
Zip Code
10029
Amiri, Anahita; Coppola, Gianfilippo; Scuderi, Soraya et al. (2018) Transcriptome and epigenome landscape of human cortical development modeled in organoids. Science 362:
Giambartolomei, Claudia; Zhenli Liu, Jimmy; Zhang, Wen et al. (2018) A Bayesian framework for multiple trait colocalization from summary association statistics. Bioinformatics 34:2538-2545
Toker, Lilah; Mancarci, Burak Ogan; Tripathy, Shreejoy et al. (2018) Transcriptomic Evidence for Alterations in Astrocytes and Parvalbumin Interneurons in Subjects With Bipolar Disorder and Schizophrenia. Biol Psychiatry 84:787-796
Huckins, L M; Hatzikotoulas, K; Southam, L et al. (2018) Investigation of common, low-frequency and rare genome-wide variation in anorexia nervosa. Mol Psychiatry 23:1169-1180
Wang, Daifeng; Liu, Shuang; Warrell, Jonathan et al. (2018) Comprehensive functional genomic resource and integrative model for the human brain. Science 362:
Mitchell, A C; Javidfar, B; Pothula, V et al. (2018) MEF2C transcription factor is associated with the genetic and epigenetic risk architecture of schizophrenia and improves cognition in mice. Mol Psychiatry 23:123-132
Bryois, Julien; Garrett, Melanie E; Song, Lingyun et al. (2018) Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia. Nat Commun 9:3121
Fazio, Leonardo; Pergola, Giulio; Papalino, Marco et al. (2018) Transcriptomic context of DRD1 is associated with prefrontal activity and behavior during working memory. Proc Natl Acad Sci U S A 115:5582-5587
Gusev, Alexander; Mancuso, Nicholas; Won, Hyejung et al. (2018) Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights. Nat Genet 50:538-548
Mitelman, Serge A; Bralet, Marie-Cecile; Mehmet Haznedar, M et al. (2018) Positron emission tomography assessment of cerebral glucose metabolic rates in autism spectrum disorder and schizophrenia. Brain Imaging Behav 12:532-546

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