title: A pattern matching approach to the automatic selection of particles from low-contrast electron micrographs.
abstract: BACKGROUND
  Structural information of macromolecular complexes provides key insights into the way they carry out their biological functions. Achieving high-resolution structural details with electron microscopy requires the identification of a large number (up to hundreds of thousands) of single particles from electron micrographs, which is a laborious task if it has to be manually done and constitutes a hurdle towards high-throughput. Automatic particle selection in micrographs is far from being settled and new and more robust algorithms are required to reduce the number of false positives and false negatives.
  
  
  RESULTS
  In this article, we introduce an automatic particle picker that learns from the user the kind of particles he is interested in. Particle candidates are quickly and robustly classified as particles or non-particles. A number of new discriminative shape-related features as well as some statistical description of the image grey intensities are used to train two support vector machine classifiers. Experimental results demonstrate that the proposed method: (i) has a considerably low computational complexity and (ii) provides results better or comparable with previously reported methods at a fraction of their computing time.
  
  
  BACKGROUND
  The algorithm is fully implemented in the open-source Xmipp package and downloadable from http://xmipp.cnb.csic.es.
authors: Biocomputing Unit, National Center of Biotechnology (CSIC), Department of Computer Science, University Autonoma de Madrid, Campus Universidad Autonoma s/n, 28049 Cantoblanco, Madrid, Spain, Department Applied Mathematics, Tel Aviv University, Ramat Aviv, Tel Aviv 69978 Israel and Bioengineering Lab, Escuela Politecnica Superior, University San Pablo CEU, 28668 Boadilla del Monte, Madrid, Spain.
authors: V
authors: V
authors: Abrishami
authors: A
authors: A
authors: Zaldívar-Peraza
authors: J M
authors: JM
authors: de la Rosa-Trevín
authors: J
authors: J
authors: Vargas
authors: J
authors: J
authors: Otón
authors: R
authors: R
authors: Marabini
authors: Y
authors: Y
authors: Shkolnisky
authors: J M
authors: JM
authors: Carazo
authors: C O S
authors: CO
authors: Sorzano
mesh_terms: D000256:Adenoviridae / Q000648:ultrastructure; D000465:Algorithms; D057205:Automation, Laboratory / Q000379:methods*; D004265:DNA Helicases / Q000648:ultrastructure; D007091:Image Processing, Computer-Assisted / Q000379:methods; D046911:Macromolecular Substances; D008854:Microscopy, Electron; D010316:Particle Size
chemical_list: D046911:Macromolecular Substances; D004265:DNA Helicases