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Statistical approach to the analysis of cell desynchronization data
Authors:Edoardo Milotti  Alessio Del Fabbro  Chiara Dalla Pellegrina  Roberto Chignola  
Institution:aDipartimento di Fisica, Università di Trieste, Via Valerio, 2–I-34127 Trieste, Italy;bI.N.F.N.–Sezione di Trieste, Italy;cDipartimento Scientifico e Tecnologico, Facoltà di Scienze MM.FF.NN., Università di Verona, Strada Le Grazie, 15 - CV1, I-37134 Verona, Italy;dFacoltà di Scienze Motorie, Università di Verona, I-37134 Verona, Italy
Abstract:Experimental measurements on semi-synchronous tumor cell populations show that after a few cell cycles they desynchronize completely, and this desynchronization reflects the intercell variability of cell-cycle duration. It is important to identify the sources of randomness that desynchronize a population of cells living in a homogeneous environment: for example, being able to reduce randomness and induce synchronization would aid in targeting tumor cells with chemotherapy or radiotherapy. Here we describe a statistical approach to the analysis of the desynchronization measurements that is based on minimal modeling hypotheses, and can be derived from simple heuristics. We use the method to analyze existing desynchronization data and to draw conclusions on the randomness of cell growth and proliferation.
Keywords:Synchronized cell populations
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