title: An automatic tool to analyze and cluster macromolecular conformations based on self-organizing maps.
abstract: BACKGROUND
  Sampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise; in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons.
  
  
  RESULTS
  We present here a python library implementing the full SOM analysis workflow. Large SOMs can readily be applied on heavy data sets. Coupled with visualization tools they have very interesting properties. Descriptors for each conformation of a trajectory are calculated and mapped onto a 3D landscape, the U-matrix, reporting the distance between neighboring neurons. To delineate clusters, we developed the flooding algorithm, which hierarchically identifies local basins of the U-matrix from the global minimum to the maximum.
  
  
  METHODS
  The python implementation of the SOM library is freely available on github: https://github.com/bougui505/SOM.
  
  
  BACKGROUND
  michael.nilges@pasteur.fr or guillaume.bouvier@pasteur.fr
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3528; Département de Biologie Structurale et Chimie; F-75015, Paris, France.
authors.forename: Guillaume
authors.initials: G
authors.lastname: Bouvier
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3528; Département de Biologie Structurale et Chimie; F-75015, Paris, France.
authors.forename: Nathan
authors.initials: N
authors.lastname: Desdouits
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3528; Département de Biologie Structurale et Chimie; F-75015, Paris, France.
authors.forename: Mathias
authors.initials: M
authors.lastname: Ferber
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3528; Département de Biologie Structurale et Chimie; F-75015, Paris, France.
authors.forename: Arnaud
authors.initials: A
authors.lastname: Blondel
authors.affiliation: Institut Pasteur, Unité de Bioinformatique Structurale; CNRS UMR 3528; Département de Biologie Structurale et Chimie; F-75015, Paris, France.
authors.forename: Michael
authors.initials: M
authors.lastname: Nilges
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D012984:Software