Literature DB >> 21625289

A Graphical Model to Determine the Subcellular Protein Location in Artificial Tissues.

Estelle Glory-Afshar1, Elvira Osuna-Highley, Brian Granger, Robert F Murphy.   

Abstract

Location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform comprehensive analysis of all protein location patterns, automated methods are needed. With the goal of extending automated subcellular location pattern analysis methods to high resolution images of tissues, 3D confocal microscope images of polarized CaCo2 cells immunostained for various proteins were collected. A three-color staining protocol was developed that permits parallel imaging of proteins of interest as well as DNA and the actin cytoskeleton. The collection is composed of 11 to 21 images for each of the 9 proteins that depict major subcellular patterns. A classifier was trained to recognize the subcellular location pattern of segmented cells with an accuracy of 89.2%. Using the Prior Updating method allowed improvement of this accuracy to 99.6%. This study demonstrates the benefit of using a graphical model approach for improving the pattern classification in tissue images.

Entities:  

Year:  2010        PMID: 21625289      PMCID: PMC3103227          DOI: 10.1109/ISBI.2010.5490167

Source DB:  PubMed          Journal:  Proc IEEE Int Symp Biomed Imaging        ISSN: 1945-7928


  6 in total

1.  Characterization of the TGN exit signal of the human mannose 6-phosphate uncovering enzyme.

Authors:  Prashant Nair; Beat E Schaub; Kai Huang; Xiang Chen; Robert F Murphy; Janice M Griffith; Hans J Geuze; Jack Rohrer
Journal:  J Cell Sci       Date:  2005-07-01       Impact factor: 5.285

Review 2.  Automated subcellular location determination and high-throughput microscopy.

Authors:  Estelle Glory; Robert F Murphy
Journal:  Dev Cell       Date:  2007-01       Impact factor: 12.270

3.  Automated recognition of patterns characteristic of subcellular structures in fluorescence microscopy images.

Authors:  M V Boland; M K Markey; R F Murphy
Journal:  Cytometry       Date:  1998-11-01

4.  A human protein atlas for normal and cancer tissues based on antibody proteomics.

Authors:  Mathias Uhlén; Erik Björling; Charlotta Agaton; Cristina Al-Khalili Szigyarto; Bahram Amini; Elisabet Andersen; Ann-Catrin Andersson; Pia Angelidou; Anna Asplund; Caroline Asplund; Lisa Berglund; Kristina Bergström; Harry Brumer; Dijana Cerjan; Marica Ekström; Adila Elobeid; Cecilia Eriksson; Linn Fagerberg; Ronny Falk; Jenny Fall; Mattias Forsberg; Marcus Gry Björklund; Kristoffer Gumbel; Asif Halimi; Inga Hallin; Carl Hamsten; Marianne Hansson; My Hedhammar; Görel Hercules; Caroline Kampf; Karin Larsson; Mats Lindskog; Wald Lodewyckx; Jan Lund; Joakim Lundeberg; Kristina Magnusson; Erik Malm; Peter Nilsson; Jenny Odling; Per Oksvold; Ingmarie Olsson; Emma Oster; Jenny Ottosson; Linda Paavilainen; Anja Persson; Rebecca Rimini; Johan Rockberg; Marcus Runeson; Asa Sivertsson; Anna Sköllermo; Johanna Steen; Maria Stenvall; Fredrik Sterky; Sara Strömberg; Mårten Sundberg; Hanna Tegel; Samuel Tourle; Eva Wahlund; Annelie Waldén; Jinghong Wan; Henrik Wernérus; Joakim Westberg; Kenneth Wester; Ulla Wrethagen; Lan Lan Xu; Sophia Hober; Fredrik Pontén
Journal:  Mol Cell Proteomics       Date:  2005-08-27       Impact factor: 5.911

5.  A framework for the automated analysis of subcellular patterns in human protein atlas images.

Authors:  Justin Newberg; Robert F Murphy
Journal:  J Proteome Res       Date:  2008-04-25       Impact factor: 4.466

6.  A graphical model approach to automated classification of protein subcellular location patterns in multi-cell images.

Authors:  Shann-Ching Chen; Robert F Murphy
Journal:  BMC Bioinformatics       Date:  2006-02-23       Impact factor: 3.169

  6 in total
  1 in total

1.  Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments.

Authors:  Diego Morone; Alessandro Marazza; Timothy J Bergmann; Maurizio Molinari
Journal:  Mol Biol Cell       Date:  2020-05-13       Impact factor: 4.138

  1 in total

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