title: CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data.
abstract: BACKGROUND
  Simple bioinformatic tools are frequently used to analyse time-series datasets regardless of their ability to deal with transient phenomena, limiting the meaningful information that may be extracted from them. This situation requires the development and exploitation of tailor-made, easy-to-use and flexible tools designed specifically for the analysis of time-series datasets.
  
  
  RESULTS
  We present a novel statistical application called CLUSTERnGO, which uses a model-based clustering algorithm that fulfils this need. This algorithm involves two components of operation. Component 1 constructs a Bayesian non-parametric model (Infinite Mixture of Piecewise Linear Sequences) and Component 2, which applies a novel clustering methodology (Two-Stage Clustering). The software can also assign biological meaning to the identified clusters using an appropriate ontology. It applies multiple hypothesis testing to report the significance of these enrichments. The algorithm has a four-phase pipeline. The application can be executed using either command-line tools or a user-friendly Graphical User Interface. The latter has been developed to address the needs of both specialist and non-specialist users. We use three diverse test cases to demonstrate the flexibility of the proposed strategy. In all cases, CLUSTERnGO not only outperformed existing algorithms in assigning unique GO term enrichments to the identified clusters, but also revealed novel insights regarding the biological systems examined, which were not uncovered in the original publications.
  
  
  METHODS
  The C++ and QT source codes, the GUI applications for Windows, OS X and Linux operating systems and user manual are freely available for download under the GNU GPL v3 license at http://www.cmpe.boun.edu.tr/content/CnG.
  
  
  BACKGROUND
  sgo24@cam.ac.uk
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Computer Engineering.
authors.forename: Işık Barış
authors.initials: IB
authors.lastname: Fidaner
authors.affiliation: Department of Chemical Engineering, Bogazici University, Istanbul, Turkey and Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Ayca
authors.initials: A
authors.lastname: Cankorur-Cetinkaya
authors.affiliation: Department of Chemical Engineering, Bogazici University, Istanbul, Turkey and Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Duygu
authors.initials: D
authors.lastname: Dikicioglu
authors.affiliation: Department of Chemical Engineering, Bogazici University, Istanbul, Turkey and.
authors.forename: Betul
authors.initials: B
authors.lastname: Kirdar
authors.affiliation: Department of Computer Engineering.
authors.forename: Ali Taylan
authors.initials: AT
authors.lastname: Cemgil
authors.affiliation: Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, UK.
authors.forename: Stephen G
authors.initials: SG
authors.lastname: Oliver
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016000:Cluster Analysis; D020869:Gene Expression Profiling / Q000379:methods*; D015233:Models, Statistical; D012984:Software