title: SpaCEM3: a software for biological module detection when data is incomplete, high dimensional and dependent.
abstract: CONCLUSIONS
  Among classical methods for module detection, SpaCEM(3) provides ad hoc algorithms that were shown to be particularly well adapted to specific features of biological data: high-dimensionality, interactions between components (genes) and integrated treatment of missingness in observations. The software, currently in its version 2.0, is developed in C++ and can be used either via command line or with the GUI under Linux and Windows environments.
  
  
  BACKGROUND
  The SpaCEM(3) software, a documentation and datasets are available from http://spacem3.gforge.inria.fr/.
authors.affiliation: INRA Toulouse, Castanet Tolosan, France. matthieu.vignes@toulouse.inra.fr
authors.forename: Matthieu
authors.initials: M
authors.lastname: Vignes
authors.forename: Juliette
authors.initials: J
authors.lastname: Blanchet
authors.forename: Damien
authors.initials: D
authors.lastname: Leroux
authors.forename: Florence
authors.initials: F
authors.lastname: Forbes
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D023281:Genomics / Q000379:methods; D008390:Markov Chains; D008954:Models, Biological; D011381:Programming Languages; D012984:Software