ArticleBioinformatics (Oxford, England)2010
Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing.
Article in Bioinformatics (Oxford, England), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 49 citations in OpenAlex.
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- Quantitative analysis of F-actin redistribution in astrocytoma cells treated with candidate pharmaceuticals.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2014Article
- Determining the subcellular location of new proteins from microscope images using local features.Bioinformatics (Oxford, England) · 2013Article
- FuncISH: learning a functional representation of neural ISH images.Bioinformatics (Oxford, England) · 2013Article
- Revealing functionally coherent subsets using a spectral clustering and an information integration approach.BMC systems biology · 2012Article
- Automated analysis and reannotation of subcellular locations in confocal images from the Human Protein Atlas.PloS one · 2012Article
- CellOrganizer: Image-derived models of subcellular organization and protein distribution.Methods in cell biology · 2012Article
- Image-derived, three-dimensional generative models of cellular organization.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2011Article
- The Plant Organelles Database 2 (PODB2): an updated resource containing movie data of plant organelle dynamics.Plant & cell physiology · 2011Article
- Communicating subcellular distributions.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2010Review
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
motivationProteins exhibit complex subcellular distributions, which may include localizing in more than one organelle and varying in location depending on the cell physiology. Estimating the amount of protein distributed in each subcellular location is essential for quantitative understanding and modeling of protein dynamics and how they affect cell behaviors. We have previously described automated methods using fluorescent microscope images to determine the fractions of protein fluorescence in various subcellular locations when the basic locations in which a protein can be present are known. As this set of basic locations may be unknown (especially for studies on a proteome-wide scale), we here describe unsupervised methods to identify the fundamental patterns from images of mixed patterns and estimate the fractional composition of them.
methodsWe developed two approaches to the problem, both based on identifying types of objects present in images and representing patterns by frequencies of those object types. One is a basis pursuit method (which is based on a linear mixture model), and the other is based on latent Dirichlet allocation (LDA). For testing both approaches, we used images previously acquired for testing supervised unmixing methods. These images were of cells labeled with various combinations of two organelle-specific probes that had the same fluorescent properties to simulate mixed patterns of subcellular location.
resultsWe achieved 0.80 and 0.91 correlation between estimated and underlying fractions of the two probes (fundamental patterns) with basis pursuit and LDA approaches, respectively, indicating that our methods can unmix the complex subcellular distribution with reasonably high accuracy. AVAILABILITY: http://murphylab.web.cmu.edu/software.
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