title: The Sleipnir library for computational functional genomics.
abstract: BACKGROUND
  Biological data generation has accelerated to the point where hundreds or thousands of whole-genome datasets of various types are available for many model organisms. This wealth of data can lead to valuable biological insights when analyzed in an integrated manner, but the computational challenge of managing such large data collections is substantial. In order to mine these data efficiently, it is necessary to develop methods that use storage, memory and processing resources carefully.
  
  
  RESULTS
  The Sleipnir C++ library implements a variety of machine learning and data manipulation algorithms with a focus on heterogeneous data integration and efficiency for very large biological data collections. Sleipnir allows microarray processing, functional ontology mining, clustering, Bayesian learning and inference and support vector machine tasks to be performed for heterogeneous data on scales not previously practical. In addition to the library, which can easily be integrated into new computational systems, prebuilt tools are provided to perform a variety of common tasks. Many tools are multithreaded for parallelization in desktop or high-throughput computing environments, and most tasks can be performed in minutes for hundreds of datasets using a standard personal computer.
  
  
  BACKGROUND
  Source code (C++) and documentation are available at http://function.princeton.edu/sleipnir and compiled binaries are available from the authors on request.
authors.affiliation: Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, NJ 08540, USA.
authors.forename: Curtis
authors.initials: C
authors.lastname: Huttenhower
authors.forename: Mark
authors.initials: M
authors.lastname: Schroeder
authors.forename: Maria D
authors.initials: MD
authors.lastname: Chikina
authors.forename: Olga G
authors.initials: OG
authors.lastname: Troyanskaya
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D019295:Computational Biology / Q000379:methods*; D003628:Database Management Systems; D030541:Databases, Genetic; D023281:Genomics / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D012984:Software; D014584:User-Computer Interface