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Provision of an integrated data analysis platform for computational neuroscience experiments

Provision of an integrated data analysis platform for computational neuroscience experiments Purpose – The purpose of this paper is to provide an integrated analysis base to facilitate computational neuroscience experiments, following a user‐led approach to provide access to the integrated neuroscience data and to enable the analyses demanded by the biomedical research community. Design/methodology/approach – The design and development of the N4U analysis base and related information services addresses the existing research and practical challenges by offering an integrated medical data analysis environment with the necessary building blocks for neuroscientists to optimally exploit neuroscience workflows, large image data sets and algorithms to conduct analyses. Findings – The provision of an integrated e‐science environment of computational neuroimaging can enhance the prospects, speed and utility of the data analysis process for neurodegenerative diseases. Originality/value – The N4U analysis base enables conducting biomedical data analyses by indexing and interlinking the neuroimaging and clinical study data sets stored on the grid infrastructure, algorithms and scientific workflow definitions along with their associated provenance information. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Systems and Information Technology Emerald Publishing

Provision of an integrated data analysis platform for computational neuroscience experiments

Kamran Munir
Journal of Systems and Information Technology , Volume 16 (3): 20 – Aug 5, 2014
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Publisher
Emerald Publishing
Copyright
Copyright © 2014 Emerald Group Publishing Limited. All rights reserved.
ISSN
1328-7265
DOI
10.1108/JSIT-01-2014-0004
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to provide an integrated analysis base to facilitate computational neuroscience experiments, following a user‐led approach to provide access to the integrated neuroscience data and to enable the analyses demanded by the biomedical research community. Design/methodology/approach – The design and development of the N4U analysis base and related information services addresses the existing research and practical challenges by offering an integrated medical data analysis environment with the necessary building blocks for neuroscientists to optimally exploit neuroscience workflows, large image data sets and algorithms to conduct analyses. Findings – The provision of an integrated e‐science environment of computational neuroimaging can enhance the prospects, speed and utility of the data analysis process for neurodegenerative diseases. Originality/value – The N4U analysis base enables conducting biomedical data analyses by indexing and interlinking the neuroimaging and clinical study data sets stored on the grid infrastructure, algorithms and scientific workflow definitions along with their associated provenance information.

Journal

Journal of Systems and Information Technology – Emerald Publishing

Published: Aug 5, 2014

Keywords: Computational neuroscience; Data analysis; E‐Science; Data integration; Scientific workflow; Information service

References

  • Federated web‐accessible clinical data management within an extensible neuroimaging database
    Burak, I.O.; Keator, D.; Wei, D.; Fennema‐Notestine, C.; Pease, K.; Bockholt, J.; Grethe, J.
  • Efficient, distributed and interactive neuroimaging data analysis using the LONI pipeline
    Dinov, I.D.; Van Horn, J.D.; Lozev, K.M.; Magsipoc, R.; Petrosyan, P.; Liu, Z.; Mackenzie‐Graham, A.; Eggert, P.; Parker, D.S.; Toga, A.W.
  • N4U: expansion of neuGRID services and outreach to new user communities (poster)
    Frisoni, G.B.; Manset, D.; McClatchey, R.; Barkhof, F.; Cover, K.S.; Wahlund, L.O.; Finocchiaro, C.; Mangin, J.F.; Giannakopulos, P.; Toga, A.; Evans, A.; Montagnat, J.
  • BIRN: biomedical informatics research network: building a national collaboratory to hasten the derivation of new understanding and treatment of disease
    Grethe, J.S.; Baru, C.; Gupta, A.; James, M.; Ludaescher, B.; Martone, M.E.; Papadopoulos, P.M.; Peltier, S.T.; Rajasekar, A.; Santini, S.; Zaslavsky, I.N.; Ellisman, M.H.
  • Improving the analysis, storage and sharing of neuroimaging data using relational databases and distributed computing
    Hasson, U.; Skipper, J.I.; Wilde, M.J.; Nusbaum, H.C.; Small, S.L.
  • A grid‐based image archival and analysis system
    Hastings, S.; Oster, S.; Langella, S.; Kurc, T.M.; Pan, T.; Catalyurek, U.V.; Saltz, J.H.
  • Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset
    Hinrichs, C.; Singh, V.; Mukherjee, L.; Xu, G.; Chung, M.K.; Johnson, S.C.
  • The extensible neuroimaging archive toolkit
    Marcus, D.S.; Olsen, T.R.; Ramaratnam, M.; Buckner, R.L.
  • Grid‐wide neuroimaging data federation in the context of the NeuroLOG project
    Michel, F.; Gaignard, A.; Ahmad, F.; Barillot, C.; Batrancourt, B.; Dojat, M.; Gibaud, B.; Girard, P.; Godard, D.; Kassel, G.; Lingrand, D.; Malandain, G.; Montagnat, J.; Pélégrini‐Issac, M.; Pennec, X.; Rojas, B.J.; Wali, B.
  • The Alzheimer’s disease neuroimaging initiative
    Mueller, S.G.; Weiner, M.W.; Thal, L.J.; Petersen, R.C.; Jack, C.; Jagust, W.; Trojanowski, J.Q.; Toga, A.W.; Beckett, L.
  • Ontology‐driven relational query formulation using the semantic and assertional capabilities of OWL‐DL
    Munir, K.; Odeh, M.; McClatchey, R.
  • An integrated e‐science analysis base for computation neuroscience experiments and analysis
    Munir, K.; Kiani, S.L.; Hasham, K.; McClatchey, R.; Branson, A.; Shamdasani, J.
  • Grid infrastructures for computational neuroscience: the neuGRID example
    Redolfi, A.; McClatchey, R.; Anjum, A.; Zijdenbos, A.; Manset, D.; Barkhof, F.; Spenger, C.; Legré, Y.; Wahlund, L.; Barattieri di San Pietro, C.; Frisoni, G.B.
  • Neuroscience information framework
    SenseLab
  • Database‐managed grid‐enabled analysis of neuroimaging data: the CNARI framework
    Small, S.L.; Wilde, M.J.; Kenny, S.; Andric, M.; Hasson, U.
  • Semantic annotation of image processing tools
    Wali, B.; Gibaud, B.
  • Swift: fast, reliable, loosely coupled parallel computation
    Zhao, Y.; Hategan, M.; Clifford, B.; Foster, I.; von Laszewski, G.; Nefedova, V.; Raicu, I.; Stef‐Praun, T.; Wilde, M.