Quantitative analysis of dynamic association in live biological fluorescent samples.

Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional co...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Pekka Ruusuvuori, Lassi Paavolainen, Kalle Rutanen, Anita Mäki, Heikki Huttunen, Varpu Marjomäki
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3322ae2d4471497683d6a49a1555cf5b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3322ae2d4471497683d6a49a1555cf5b
record_format	dspace
spelling	oai:doaj.org-article:3322ae2d4471497683d6a49a1555cf5b2021-11-18T08:23:41ZQuantitative analysis of dynamic association in live biological fluorescent samples.1932-620310.1371/journal.pone.0094245https://doaj.org/article/3322ae2d4471497683d6a49a1555cf5b2014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24728133/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest Points registration method. Results for fixed and live experimental data shows the association method to perform comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for live cells.Pekka RuusuvuoriLassi PaavolainenKalle RutanenAnita MäkiHeikki HuttunenVarpu MarjomäkiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 4, p e94245 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Pekka Ruusuvuori Lassi Paavolainen Kalle Rutanen Anita Mäki Heikki Huttunen Varpu Marjomäki Quantitative analysis of dynamic association in live biological fluorescent samples.
description	Determining vesicle localization and association in live microscopy may be challenging due to non-simultaneous imaging of rapidly moving objects with two excitation channels. Besides errors due to movement of objects, imaging may also introduce shifting between the image channels, and traditional colocalization methods cannot handle such situations. Our approach to quantifying the association between tagged proteins is to use an object-based method where the exact match of object locations is not assumed. Point-pattern matching provides a measure of correspondence between two point-sets under various changes between the sets. Thus, it can be used for robust quantitative analysis of vesicle association between image channels. Results for a large set of synthetic images shows that the novel association method based on point-pattern matching demonstrates robust capability to detect association of closely located vesicles in live cell-microscopy where traditional colocalization methods fail to produce results. In addition, the method outperforms compared Iterated Closest Points registration method. Results for fixed and live experimental data shows the association method to perform comparably to traditional methods in colocalization studies for fixed cells and to perform favorably in association studies for live cells.
format	article
author	Pekka Ruusuvuori Lassi Paavolainen Kalle Rutanen Anita Mäki Heikki Huttunen Varpu Marjomäki
author_facet	Pekka Ruusuvuori Lassi Paavolainen Kalle Rutanen Anita Mäki Heikki Huttunen Varpu Marjomäki
author_sort	Pekka Ruusuvuori
title	Quantitative analysis of dynamic association in live biological fluorescent samples.
title_short	Quantitative analysis of dynamic association in live biological fluorescent samples.
title_full	Quantitative analysis of dynamic association in live biological fluorescent samples.
title_fullStr	Quantitative analysis of dynamic association in live biological fluorescent samples.
title_full_unstemmed	Quantitative analysis of dynamic association in live biological fluorescent samples.
title_sort	quantitative analysis of dynamic association in live biological fluorescent samples.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/3322ae2d4471497683d6a49a1555cf5b
work_keys_str_mv	AT pekkaruusuvuori quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples AT lassipaavolainen quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples AT kallerutanen quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples AT anitamaki quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples AT heikkihuttunen quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples AT varpumarjomaki quantitativeanalysisofdynamicassociationinlivebiologicalfluorescentsamples
_version_	1718421852156592128

Quantitative analysis of dynamic association in live biological fluorescent samples.

Ejemplares similares