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The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools.

Monday, May 12, 2014

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Brain Imaging Behav. 2014 Jun;8(2):311-22. doi: 10.1007/s11682-013-9248-x. Dinov ID1, Petrosyan P, Liu Z, Eggert P, Zamanyan A, Torri F, Macciardi F, Hobel S, Moon SW, Sung YH, Jiang Z, Labus J, Kurth F, Ashe-McNalley C, Mayer E, Vespa PM, Van Horn JD, Toga AW; Alzheimer’s Disease Neuroimaging Initiative. Abstract The volume, diversity and velocity of […]

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High-throughput neuroimaging-genetics computational infrastructure.

Wednesday, April 23, 2014

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Front Neuroinform. 2014 Apr 23;8:41. doi: 10.3389/fninf.2014.00041 Dinov ID, Petrosyan P, Liu Z, Eggert P, Hobel S, Vespa P, Woo Moon S, Van Horn JD, Franco J, Toga AW. Abstract Many contemporary neuroscientific investigations face significant challenges in terms of data management, computational processing, data mining, and results interpretation. These four pillars define the core […]

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Applications of the pipeline environment for visual informatics and genomics computations.

Tuesday, July 26, 2011

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BMC Bioinformatics. 2011 Jul 26;12:304. doi: 10.1186/1471-2105-12-304. Dinov ID, Torri F, Macciardi F, Petrosyan P, Liu Z, Zamanyan A, Eggert P, Pierce J, Genco A, Knowles JA, Clark AP, Van Horn JD, Ames J, Kesselman C, Toga AW. Abstract BACKGROUND: Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, […]

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Neuroimaging study designs, computational analyses and data provenance using the LONI pipeline.

Tuesday, September 28, 2010

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PLoS One. 2010 Sep 28;5(9). pii: e13070. doi: 10.1371/journal.pone.0013070. Dinov I, Lozev K, Petrosyan P, Liu Z, Eggert P, Pierce J, Zamanyan A, Chakrapani S, Van Horn J, Parker DS, Magsipoc R, Leung K, Gutman B, Woods R, Toga A. Abstract Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain […]

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Efficient, Distributed and Interactive Neuroimaging Data Analysis Using the LONI Pipeline.

Monday, July 20, 2009

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Front Neuroinform. 2009 Jul 20;3:22. doi: 10.3389/neuro.11.022.2009. eCollection 2009. Dinov ID, Van Horn JD, Lozev KM, Magsipoc R, Petrosyan P, Liu Z, Mackenzie-Graham A, Eggert P, Parker DS, Toga AW. Abstract The LONI Pipeline is a graphical environment for construction, validation and execution of advanced neuroimaging data analysis protocols (Rex et al., 2003). It enables […]

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Neuroimaging Data Provenance Using the LONI Pipeline Workflow Environment

Friday, October 17, 2008

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Lecture Notes in Computer Science Volume 5272, 2008, pp 208-220 Provenance and Annotation of Data and Processes Allan J. MacKenzie-Graham, Arash Payan, Ivo D. Dinov, John D. Van Horn, Arthur W. Toga Abstract Provenance, the description of the history of a set of data, has become important in the neurosciences with the proliferation of research […]

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Provenance in neuroimaging

Friday, August 1, 2008

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NeuroImage Volume 42, Issue 1, 1 August 2008, Pages 178–195 http://dx.doi.org/10.1016/j.neuroimage.2008.04.186 Allan J. MacKenzie-Graham, John D. Van Horn, Roger P. Woods, Karen L. Crawford, Arthur W. Toga Abstract Provenance, the description of the history of a set of data, has grown more important with the proliferation of research consortia-related efforts in neuroimaging. Knowledge about the […]

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Data Provenance

Thursday, July 31, 2008

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An important aspect of provenance is the description of the subject. Subject provenance includes birth and death dates (for post-mortem studies), in addition to the age of the subject at the time of the data collection (or death).

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Welcome

Tuesday, May 13, 2008

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Welcome to our new Provenance website.

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