5
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of HeLa cells

      ,
      Bioinformatics
      Oxford University Press (OUP)

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Assessment of protein subcellular location is crucial to proteomics efforts since localization information provides a context for a protein's sequence, structure, and function. The work described below is the first to address the subcellular localization of proteins in a quantitative, comprehensive manner. Images for ten different subcellular patterns (including all major organelles) were collected using fluorescence microscopy. The patterns were described using a variety of numeric features, including Zernike moments, Haralick texture features, and a set of new features developed specifically for this purpose. To test the usefulness of these features, they were used to train a neural network classifier. The classifier was able to correctly recognize an average of 83% of previously unseen cells showing one of the ten patterns. The same classifier was then used to recognize previously unseen sets of homogeneously prepared cells with 98% accuracy. Algorithms were implemented using the commercial products Matlab, S-Plus, and SAS, as well as some functions written in C. The scripts and source code generated for this work are available at http://murphylab.web.cmu.edu/software. murphy@cmu.edu

          Related collections

          Author and article information

          Journal
          Bioinformatics
          Bioinformatics
          Oxford University Press (OUP)
          1367-4803
          1460-2059
          December 01 2001
          December 01 2001
          : 17
          : 12
          : 1213-1223
          Article
          10.1093/bioinformatics/17.12.1213
          11751230
          4102c8a0-75db-401c-9b1b-f70c491f13a1
          © 2001
          History

          Comments

          Comment on this article