ArticleBiophysical journal2004
Automatic and quantitative measurement of protein-protein colocalization in live cells.
Article in Biophysical journal, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 863 papers.
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Who cites it
863 citing papers in PubMed.
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803 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
We introduce a novel statistical approach that quantifies, for the first time, the amount of colocalization of two fluorescent-labeled proteins in an image automatically, removing the bias of visual interpretation. This is done by estimating simultaneously the maximum threshold of intensity for each color below which pixels do not show any statistical correlation. The sensitivity of the method was illustrated on simulated data by statistically confirming the existence of true colocalization in images with as little as 3% colocalization. This method was then tested on a large three-dimensional set of fixed cells cotransfected with CFP/YFP pairs of proteins that either co-compartmentalized, interacted, or were just randomly localized in the nucleolus. In this test, the algorithm successfully distinguished random color overlap from colocalization due to either co-compartmentalization or interaction, and results were verified by fluorescence resonance energy transfer. The accuracy and consistency of our algorithm was further illustrated by measuring, for the first time in live cells, the dissociation rate (k(d)) of the HIV-1 Rev/CRM1 export complex induced by the cytotoxin leptomycin B. Rev/CRM1 colocalization in nucleoli dropped exponentially after addition of leptomycin B at a rate of 1.25 x 10(-3) s(-1). More generally, this algorithm can be used to answer a variety of biological questions involving protein-protein interactions or co-compartmentalization and can be generalized to colocalization of more than two colors.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.