Linked Life Data

21519967

Source:http://linkedlifedata.com/resource/pubmed/id/21519967

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2011-6-28
pubmed:abstractText
The large amount of data generated using matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) poses a challenge for data analysis. In fact, generally about 1.10(8)-1.10(9) values (m/z, I) are stored after a single MALDI-MSI experiment. This imposes processing techniques using dedicated informatics tools to be used since manual data interpretation is excluded. This work proposes and summarizes an approach that utilizes a multivariable analysis of MSI data. The multivariate analysis, such as principal component analysis-symbolic discriminant analysis, can remove and highlight specific m/z from the spectra in a specific region of interest. This approach facilitates data processing and provides better reproducibility, and thus, broadband acquisition for MALDI-MSI should be considered an effective tool to highlight biomarkers of interest. Additionally, we demonstrate the importance of the hierarchical classification of biomarkers by analyzing studies of clusters obtained either from digested or undigested tissues and using bottom-up and in-source decay strategies for in-tissue protein identification. This provides the possibility for the rapid identification of specific markers from different histological samples and their direct localization in tissues. We present an example from a prostate cancer study using formalin-fixed paraffin-embedded tissue.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1618-2650
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
401
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
149-65
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Multivariate analyses for biomarkers hunting and validation through on-tissue bottom-up or in-source decay in MALDI-MSI: application to prostate cancer.
pubmed:affiliation
MALDI Imaging team, Laboratoire de Spectrométrie de Masse Biologique Fondamentale et Appliquée (FABMS), EA 4550, Université Nord de France, Université Lille 1, Villeneuve d'Ascq, France.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Validation Studies