The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools.
The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools...
| Publicado en: | Brain Imaging & Behavior Vol. 8; no. 2; pp. 311 - 323 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Jun2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=103821351&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 103821351 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 19317557 3GSC jtl: Brain Imaging & Behavior issn: 19317557 maglogo: N pubinfo: dt: Jun2014 vid: 8 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 103821351 NLM23975276 2012571229 10.1007/s11682-013-9248-x NLM23975276 PMC3933453 103821351 ppf: 311 ppct: 12 formats: fmt: @attributes: type: P tig: atl: The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools. aug: au: Dinov, Ivo D Petrosyan, Petros Liu, Zhizhong Eggert, Paul Zamanyan, Alen Torri, Federica Macciardi, Fabio Hobel, Sam Moon, Seok Woo Sung, Young Hee Jiang, Zhiguo Labus, Jennifer Kurth, Florian Ashe-McNalley, Cody Mayer, Emeran Vespa, Paul M Van Horn, John D Toga, Arthur W affil: Laboratory of Neuro Imaging (LONI), David Geffen School of Medicine at UCLA, University of California, Los Angeles, 635 S. Charles Young Drive, Suite 225, Los Angeles, CA, 90095-7334, USA, dinov@ucla.edu. sug: subj: Algorithms Genomics Methods Internet Neuroradiography Methods Software Systems Analysis Alzheimer's Disease Alzheimer's Disease Pathology Alzheimer's Disease Physiopathology Brain Pathology Brain Physiopathology Brain Injuries Pathology Brain Injuries Physiopathology Chronic Pain Complications Chronic Pain Pathology Bioinformatics Methods Female Sequence Analysis Methods Communication Methods Irritable Bowel Syndrome Complications Irritable Bowel Syndrome Pathology Male Middle Age Middle Aged: 45-64 years Female Male ab: The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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