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

ABSTRACT:

Motivation

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

SUBMITTER: Fidaner IB 

PROVIDER: S-EPMC4734040 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature