CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data | Zendy

Işık Barış Fidaner | Zendy; Ayca CankorurCetinkaya | Zendy; Duygu Dikicioǧlu | Zendy; Betül Kırdar | Zendy; Ali Taylan Cemgil | Zendy; Stephen G. Oliver | Zendy

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CLUSTERnGO: a user-defined modelling platform for two-stage clustering of time-series data

Author(s) -

Işık Barış Fidaner,

Ayca CankorurCetinkaya,

Duygu Dikicioǧlu,

Betül Kırdar,

Ali Taylan Cemgil,

Stephen G. Oliver

Publication year - 2015

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv532

Subject(s) - computer science , cluster analysis , graphical user interface , data mining , component (thermodynamics) , pipeline (software) , flexibility (engineering) , interface (matter) , software , bayesian probability , machine learning , artificial intelligence , programming language , statistics , physics , mathematics , bubble , maximum bubble pressure method , parallel computing , thermodynamics

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.

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