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dc.contributor.authorGuirado, Ramón
dc.contributor.authorCarceller, Héctor
dc.contributor.authorCastillo-Gomez, Esther
dc.contributor.authorCastrén, Eero
dc.contributor.authorNacher, Juan
dc.date.accessioned2018-12-12T08:07:20Z
dc.date.available2018-12-12T08:07:20Z
dc.date.issued2018-06
dc.identifier.citationGUIRADO, Ramón; CARCELLER, Héctor; CASTILLO-GOMEZ, Esther; CASTRÉN, Eero; NACHER, Juan (2018). Automated analysis of images for molecular quantification in immunohistochemistry. Heliyon, v. 4, issue 6, p. article number e00669ca_CA
dc.identifier.urihttp://hdl.handle.net/10234/178022
dc.description.abstractThe quantification of the expression of different molecules is a key question in both basic and applied sciences. While protein quantification through molecular techniques leads to the loss of spatial information and resolution, immunohistochemistry is usually associated with time-consuming image analysis and human bias. In addition, the scarce automatic software analysis is often proprietary and expensive and relies on a fixed threshold binarization. Here we describe and share a set of macros ready for automated fluorescence analysis of large batches of fixed tissue samples using FIJI/ImageJ. The quantification of the molecules of interest are based on an automatic threshold analysis of immunofluorescence images to automatically identify the top brightest structures of each image. These macros measure several parameters commonly quantified in basic neuroscience research, such as neuropil density and fluorescence intensity of synaptic puncta, perisomatic innervation and col-localization of different molecules and analysis of the neurochemical phenotype of neuronal subpopulations. In addition, these same macro functions can be easily modified to improve similar analysis of fluorescent probes in human biopsies for diagnostic purposes based on the expression patterns of several molecules.ca_CA
dc.format.extent16 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherElsevierca_CA
dc.relation.isPartOfHeliyon (2018), v. 4, issue 6ca_CA
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectNeuroscienceca_CA
dc.subjectBioinformaticsca_CA
dc.titleAutomated analysis of images for molecular quantification in immunohistochemistryca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttps://doi.org/10.1016/j.heliyon.2018.e00669
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_CA
dc.relation.publisherVersionhttps://www.sciencedirect.com/science/article/pii/S2405844018310508ca_CA
dc.type.versioninfo:eu-repo/semantics/publishedVersionca_CA


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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