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Main Menu - Block
- Overview
- Anatomy and Histology
- Annotation & Analytics
- Cell and Tissue Culture
- Cryo-Electron Microscopy
- Drosophila Resources
- Electron Microscopy
- Flow Cytometry Shared Resource (FCSR)
- Gene Targeting and Transgenics
- Janelia Experimental Technology
- Light Microscopy
- Media Prep
- Molecular Biology
- Project Technical Resources
- Quantitative Genomics
- Scientific Computing Software
- Scientific Computing Systems
- Viral Tools
- Vivarium
Abstract
Clusters of time series data may change location and memberships over time; in gene expression data, this occurs as groups of genes or samples respond differently to stimuli or experimental conditions at different times. In order to uncover this underlying temporal structure, we consider dynamic clusters with time-dependent parameters which split and merge over time, enabling cluster memberships to change. These interesting time-dependent structures are useful in understanding the development of organisms or complex organs, and could not be identified using traditional clustering methods. In cell cycle data, these time-dependent structure may provide links between genes and stages of the cell cycle, whilst in developmental data sets they may highlight key developmental transitions.
PMID: 24131050 [PubMed - indexed for MEDLINE]
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