Human Neuroimaging as a “Big Data” Science
Identifieur interne : 000435 ( Pmc/Corpus ); précédent : 000434; suivant : 000436Human Neuroimaging as a “Big Data” Science
Auteurs : John Darrell Van Horn ; Arthur W. TogaSource :
- Brain imaging and behavior [ 1931-7557 ] ; 2014.
Abstract
The maturation of
Url:
DOI: 10.1007/s11682-013-9255-y
PubMed: 24113873
PubMed Central: 3983169
Links to Exploration step
PMC:3983169Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Human Neuroimaging as a “Big Data” Science</title><author><name sortKey="Van Horn, John Darrell" sort="Van Horn, John Darrell" uniqKey="Van Horn J" first="John Darrell" last="Van Horn">John Darrell Van Horn</name></author><author><name sortKey="Toga, Arthur W" sort="Toga, Arthur W" uniqKey="Toga A" first="Arthur W." last="Toga">Arthur W. Toga</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">24113873</idno><idno type="pmc">3983169</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3983169</idno><idno type="RBID">PMC:3983169</idno><idno type="doi">10.1007/s11682-013-9255-y</idno><date when="2014">2014</date><idno type="wicri:Area/Pmc/Corpus">000435</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Human Neuroimaging as a “Big Data” Science</title><author><name sortKey="Van Horn, John Darrell" sort="Van Horn, John Darrell" uniqKey="Van Horn J" first="John Darrell" last="Van Horn">John Darrell Van Horn</name></author><author><name sortKey="Toga, Arthur W" sort="Toga, Arthur W" uniqKey="Toga A" first="Arthur W." last="Toga">Arthur W. Toga</name></author></analytic><series><title level="j">Brain imaging and behavior</title><idno type="ISSN">1931-7557</idno><idno type="eISSN">1931-7565</idno><imprint><date when="2014">2014</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">The maturation of <italic>in vivo</italic> neuroimaging has lead to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of “big data”. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a mutifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociologial and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, “big data” can become “big” brain science.</p></div></front></TEI><pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">101300405</journal-id><journal-id journal-id-type="pubmed-jr-id">34269</journal-id><journal-id journal-id-type="nlm-ta">Brain Imaging Behav</journal-id><journal-id journal-id-type="iso-abbrev">Brain Imaging Behav</journal-id><journal-title-group><journal-title>Brain imaging and behavior</journal-title></journal-title-group><issn pub-type="ppub">1931-7557</issn><issn pub-type="epub">1931-7565</issn></journal-meta><article-meta><article-id pub-id-type="pmid">24113873</article-id><article-id pub-id-type="pmc">3983169</article-id><article-id pub-id-type="doi">10.1007/s11682-013-9255-y</article-id><article-id pub-id-type="manuscript">NIHMS515100</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Human Neuroimaging as a “Big Data” Science</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Van Horn</surname><given-names>John Darrell</given-names></name><xref ref-type="corresp" rid="CR1">*</xref></contrib><contrib contrib-type="author"><name><surname>Toga</surname><given-names>Arthur W.</given-names></name></contrib><aff id="A1">The Institute for Neuroimaging and Informatics Keck School of Medicine of USC University of Southern California 2001 North Soto Street - Room 102, MC 9232 Los Angeles, CA 90089-9235,<email>toga@usc.edu</email></aff></contrib-group><author-notes><corresp id="CR1"><label>*</label>Corresponding author Phone: (323) 442-7246 <email>jvanhorn@usc.edu</email></corresp></author-notes><pub-date pub-type="nihms-submitted"><day>17</day><month>10</month><year>2013</year></pub-date><pub-date pub-type="ppub"><month>6</month><year>2014</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>6</month><year>2014</year></pub-date><volume>8</volume><issue>2</issue><fpage>323</fpage><lpage>331</lpage><pmc-comment>elocation-id from pubmed: 10.1007/s11682-013-9255-y</pmc-comment>
<abstract><p id="P1">The maturation of <italic>in vivo</italic> neuroimaging has lead to incredible quantities of digital information about the human brain. While much is made of the data deluge in science, neuroimaging represents the leading edge of this onslaught of “big data”. A range of neuroimaging databasing approaches has streamlined the transmission, storage, and dissemination of data from such brain imaging studies. Yet few, if any, common solutions exist to support the science of neuroimaging. In this article, we discuss how modern neuroimaging research represents a mutifactorial and broad ranging data challenge, involving the growing size of the data being acquired; sociologial and logistical sharing issues; infrastructural challenges for multi-site, multi-datatype archiving; and the means by which to explore and mine these data. As neuroimaging advances further, e.g. aging, genetics, and age-related disease, new vision is needed to manage and process this information while marshalling of these resources into novel results. Thus, “big data” can become “big” brain science.</p></abstract></article-meta></front></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Ticri/CIDE/explor/CyberinfraV1/Data/Pmc/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000435 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd -nk 000435 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Ticri/CIDE
|area= CyberinfraV1
|flux= Pmc
|étape= Corpus
|type= RBID
|clé= PMC:3983169
|texte= Human Neuroimaging as a “Big Data” Science
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/RBID.i -Sk "pubmed:24113873" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd \
| NlmPubMed2Wicri -a CyberinfraV1
| This area was generated with Dilib version V0.6.25. |  |