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Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering by Shanaz A Ghandhi; Anshu Sinha; Marianthi Markatou; Sally A Amundson is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering about?

## Background The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM). ## Results While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either

Who reads Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering?

Author

Shanaz A Ghandhi; Anshu Sinha; Marianthi Markatou; Sally A Amundson

Publisher

BioMed Central; Springer (Biomed Central Ltd.); London: BioMed Central, 2000-; Springer Science and Business Media LLC; Society for Mining, Metallurgy and Exploration Inc. (ISSN 1471-2164)

Published

2011

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)