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ABSTRACT: 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 simil
SUBMITTER: Ghandhi SA
PROVIDER: S-EPMC3022823 | biostudies-literature | 2011 Jan
REPOSITORIES: biostudies-literature