title: Efficient initial volume determination from electron microscopy images of single particles.
abstract: BACKGROUND
  Structural information of macromolecular complexes provides key insights into the way they carry out their biological functions. The reconstruction process leading to the final 3D map requires an approximate initial model. Generation of an initial model is still an open and challenging problem in single-particle analysis.
  
  
  RESULTS
  We present a fast and efficient approach to obtain a reliable, low-resolution estimation of the 3D structure of a macromolecule, without any a priori knowledge, addressing the well-known issue of initial volume estimation in the field of single-particle analysis. The input of the algorithm is a set of class average images obtained from individual projections of a biological object at random and unknown orientations by transmission electron microscopy micrographs. The proposed method is based on an initial non-lineal dimensionality reduction approach, which allows to automatically selecting representative small sets of class average images capturing the most of the structural information of the particle under study. These reduced sets are then used to generate volumes from random orientation assignments. The best volume is determined from these guesses using a random sample consensus (RANSAC) approach. We have tested our proposed algorithm, which we will term 3D-RANSAC, with simulated and experimental data, obtaining satisfactory results under the low signal-to-noise conditions typical of cryo-electron microscopy.
  
  
  BACKGROUND
  The algorithm is freely available as part of the Xmipp 3.1 package [http://xmipp.cnb.csic.es].
  
  
  BACKGROUND
  jvargas@cnb.csic.es
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors: Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/Darwin 3 and Escuela Politécnica Superior, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente, 28049, Cantoblanco (Madrid), Spain.
authors: Javier
authors: J
authors: Vargas
authors: Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/Darwin 3 and Escuela Politécnica Superior, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente, 28049, Cantoblanco (Madrid), Spain.
authors: Ana-Lucia
authors: AL
authors: Álvarez-Cabrera
authors: Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/Darwin 3 and Escuela Politécnica Superior, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente, 28049, Cantoblanco (Madrid), Spain.
authors: Roberto
authors: R
authors: Marabini
authors: Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/Darwin 3 and Escuela Politécnica Superior, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente, 28049, Cantoblanco (Madrid), Spain.
authors: Jose M
authors: JM
authors: Carazo
authors: Biocomputing Unit, Centro Nacional de Biotecnología-CSIC, C/Darwin 3 and Escuela Politécnica Superior, Universidad Autónoma de Madrid, C/Francisco Tomás y Valiente, 28049, Cantoblanco (Madrid), Spain.
authors: C O S
authors: CO
authors: Sorzano
mesh_terms: D000465:Algorithms; D021621:Imaging, Three-Dimensional / Q000379:methods*; D046911:Macromolecular Substances / Q000737:chemistry; D046529:Microscopy, Electron, Transmission / Q000379:methods*; D008958:Models, Molecular; D013997:Time Factors
chemical_list: D046911:Macromolecular Substances