tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.

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Title: tranSMART-XNAT Connector tranSMART-XNAT connector-image selection based on clinical phenotypes and genetic profiles.
Author(s): He, S
Yong, M
Matthews, PM
Guo, Y
Item Type: Journal Article
Abstract: MOTIVATION: TranSMART has a wide range of functionalities for translational research and a large user community, but it does not support imaging data. In this context, imaging data typically includes 2D or 3D sets of magnitude data and metadata information. Imaging data may summarise complex feature descriptions in a less biased fashion than user defined plain texts and numeric numbers. Imaging data also is contextualised by other data sets and may be analysed jointly with other data that can explain features or their variation. RESULTS: Here we describe the tranSMART-XNAT Connector we have developed. This connector consists of components for data capture, organisation and analysis. Data capture is responsible for imaging capture either from PACS system or directly from an MRI scanner, or from raw data files. Data are organised in a similar fashion as tranSMART and are stored in a format that allows direct analysis within tranSMART. The connector enables selection and download of DICOM images and associated resources using subjects' clinical phenotypic and genotypic criteria. AVAILABILITY AND IMPLEMENTATION: tranSMART-XNAT connector is written in Java/Groovy/Grails. It is maintained and available for download at
Publication Date: 13-Dec-2016
Date of Acceptance: 9-Nov-2016
ISSN: 1367-4803
Publisher: Oxford University Press (OUP)
Start Page: 787
End Page: 788
Journal / Book Title: Bioinformatics
Volume: 33
Issue: 5
Copyright Statement: © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail:
Keywords: Bioinformatics
01 Mathematical Sciences
06 Biological Sciences
08 Information And Computing Sciences
Publication Status: Published
Conference Place: England
Embargo Date: 2017-12-13
Appears in Collections:Department of Medicine
Faculty of Medicine

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