title: Determining the subcellular location of new proteins from microscope images using local features.
abstract: BACKGROUND
  Evaluation of previous systems for automated determination of subcellular location from microscope images has been done using datasets in which each location class consisted of multiple images of the same representative protein. Here, we frame a more challenging and useful problem where previously unseen proteins are to be classified.
  
  
  RESULTS
  Using CD-tagging, we generated two new image datasets for evaluation of this problem, which contain several different proteins for each location class. Evaluation of previous methods on these new datasets showed that it is much harder to train a classifier that generalizes across different proteins than one that simply recognizes a protein it was trained on. We therefore developed and evaluated additional approaches, incorporating novel modifications of local features techniques. These extended the notion of local features to exploit both the protein image and any reference markers that were imaged in parallel. With these, we obtained a large accuracy improvement in our new datasets over existing methods. Additionally, these features help achieve classification improvements for other previously studied datasets.
  
  
  BACKGROUND
  The datasets are available for download at http://murphylab.web.cmu.edu/data/. The software was written in Python and C++ and is available under an open-source license at http://murphylab.web.cmu.edu/software/. The code is split into a library, which can be easily reused for other data and a small driver script for reproducing all results presented here. A step-by-step tutorial on applying the methods to new datasets is also available at that address.
  
  
  BACKGROUND
  murphy@cmu.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
authors.forename: Luis Pedro
authors.initials: LP
authors.lastname: Coelho
authors.forename: Joshua D
authors.initials: JD
authors.lastname: Kangas
authors.forename: Armaghan W
authors.initials: AW
authors.lastname: Naik
authors.forename: Elvira
authors.initials: E
authors.lastname: Osuna-Highley
authors.forename: Estelle
authors.initials: E
authors.lastname: Glory-Afshar
authors.forename: Margaret
authors.initials: M
authors.lastname: Fuhrman
authors.forename: Ramanuja
authors.initials: R
authors.lastname: Simha
authors.forename: Peter B
authors.initials: PB
authors.lastname: Berget
authors.forename: Jonathan W
authors.initials: JW
authors.lastname: Jarvik
authors.forename: Robert F
authors.initials: RF
authors.lastname: Murphy
mesh_terms: D006367:HeLa Cells; D006801:Humans; D042541:Intracellular Space / Q000737:chemistry; D018613:Microscopy, Confocal; D008856:Microscopy, Fluorescence; D011506:Proteins / Q000032:analysis*; D012984:Software
chemical_list: D011506:Proteins