Special Topic - Neuroimaging workflow design and data-mining Posted By: David Kennedy - Jan 13, 2010Tool/Resource: Journals Neuroimaging workflow design and data-mining: a Frontiers in Neuroinformatics special issue John Darrell Van Horn and Arthur W. Toga About this special topic With the increasing number of neuroimaging studies appearing yearly in the literature, the need to consider the synthesis of the underlying data into new knowledge and research directions has never been more important. The development of large-scale databases and grid-enabled computing has laid the groundwork for mining these rich datasets beyond the scope of their initial collection. Additionally, meta-analyses of the summary results contained in published research articles have provided a powerful way to explore hidden trends in the neuroscience literature. In each case, the processing of data requires a careful consideration of the individual processing steps involved and how they can be assembled into reliable workflows. In results from published studies, the manner in which data were processed may influence meta-analytic results which can have implications on clinical interpretation. Several efforts now exist that provide tools for use in the construction of data processing workflows. However, careful thought must be given to ensuring appropriate, efficient, optimal, and replicable processing. The results obtained from data-mining and meta-analysis must tell a story about a collection of existing data. Also they must suggest novel and testable hypotheses for further investigation with implications for understanding of the brain in health and disease. Where they do, these new results and interpretations often provide fresh insights into the data that extend beyond the rationale for their original collection. In this volume, we have asked leaders in the field of neuroimaging data mining and meta-analysis to provide their thoughts on methods for efficient workflow design, interoperability with large-scale databases, and to discuss their work in exploring the richness of brain imaging data as well as the literature of published research results. Articles Interactive exploration of neuroanatomical meta-spaces Shantanu H. Joshi, John Darrell Van Horn and Arthur W. Toga Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources. Henry J. Bockholt, Mark Scully, William Courtney, Srinivas Rachakonda, Adam Scott, Arvind Caprihan, Jill Fries, Ravi Kalyanam, Judith Segall, Raul de la Garza, Susan Lane and Vince D. Calhoun Bio-Swarm-Pipeline: a light-weight, extensible batch processing system for efficient biomedical data processing Xi Cheng, Ricardo Pizarro, Yunxia Tong, Brad Zoltick, Qian Luo, Daniel R. Weinberger and Venkata S. Mattay Parallel workflows for data-driven structural equation modeling in functional neuroimaging Sarah Kenny, Michael Andric, Steven M. Boker, Michael C. Neale, Michael Wilde and Steven L. Small Pooling fMRI data: meta-analysis, mega-analysis and multi-center studies Sergi G. Costafreda Derived data storage and exchange workflow for large-scale neuroimaging analyses on the BIRN grid David B. Keator, Dingying Wei, Syam Gadde, Jeremy Bockholt, Jeffrey S. Grethe, Daniel Marcus, Nicole Aucoin and Ibrahim B. Ozyurt CamBAfx: Workflow design, implementation and application for neuroimaging Cinly Ooi, Edward T. Bullmore, Alle-Meije Wink, Levent Sendur, Anna Barnes, Sophie Achard, John Aspden, Sanja Abbott, Shigang Yue, Manfred Kitzbichler, David Meunier, Voichita Maxim, Raymond Salvador, Julian Henty, Roger Tait, Naresh Subramaniam and John Suckling Visualizing data mining results with the Brede tools Finn A. Nielsen ALE meta-analysis workflows via the BrainMap database: Progress towards a probabilistic functional brain atlas Angela R. Laird, Simon B. Eickhoff, Florian Kurth, Peter M. Fox, Angela M. Uecker, Jessica A. Turner, Jennifer L. Robinson, Jack L. Lancaster and Peter T. Fox Efficient, distributed and interactive neuroimaging data analysis using the LONI pipeline Ivo Dinov, John D. Van Horn, Kamen M. Lozev, Rico Magsipoc, Petros Petrosyan, Zhizhong Liu, Allan MacKenzie-Graham, Paul Eggert, Douglas S. Parker and Arthur W. Toga An integrated object model and method framework for subject-centric e-Research applications Jason M. Lohrey, Neil E B. Killeen and Gary F. Egan |
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