Literature DB >> 19707763

Proliferation model dependence in fluctuation analysis: the neutral case.

Wolfgang P Angerer1.   

Abstract

We discuss the evaluation of Luria-Delbrück fluctuation experiments under Bellman-Harris models of cell proliferation. It is shown that under certain very natural assumptions concerning the life-time distributions and the offspring distributions of mutant and non-mutant cells, the suitably normed and centered number of mutants contained in a large culture of bacteria (or the like) converges to a certain stable random variable with index 1. The result obtains under the assumption that the mutation under consideration is "neutral" in the sense that on average and in the long run, mutant cells produce the same number of offspring as non-mutant cells.

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Year:  2009        PMID: 19707763     DOI: 10.1007/s00285-009-0294-3

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  14 in total

Review 1.  Sorting out mutation rates.

Authors:  P L Foster
Journal:  Proc Natl Acad Sci U S A       Date:  1999-07-06       Impact factor: 11.205

Review 2.  Determining mutation rates in bacterial populations.

Authors:  W A Rosche; P L Foster
Journal:  Methods       Date:  2000-01       Impact factor: 3.608

3.  Improved inference of mutation rates: II. Generalization of the Luria-Delbrück distribution for realistic cell-cycle time distributions.

Authors:  M Oprea; T B Kepler
Journal:  Theor Popul Biol       Date:  2001-02       Impact factor: 1.570

4.  A generalized Luria-Delbrück model.

Authors:  A Dewanji; E G Luebeck; S H Moolgavkar
Journal:  Math Biosci       Date:  2005-10       Impact factor: 2.144

5.  Mutations of Bacteria from Virus Sensitivity to Virus Resistance.

Authors:  S E Luria; M Delbrück
Journal:  Genetics       Date:  1943-11       Impact factor: 4.562

6.  Fluctuation analysis: the probability distribution of the number of mutants under different conditions.

Authors:  F M Stewart; D M Gordon; B R Levin
Journal:  Genetics       Date:  1990-01       Impact factor: 4.562

7.  Mutations and infinity: improved statistical methods for estimating spontaneous rates.

Authors:  A Nádas; E I Goncharova; T G Rossman
Journal:  Environ Mol Mutagen       Date:  1996       Impact factor: 3.216

8.  The distribution of the numbers of mutants in bacterial populations.

Authors:  D E LEA; C A COULSON
Journal:  J Genet       Date:  1949-12       Impact factor: 1.166

9.  Maximum likelihood estimation of spontaneous mutation rates from large initial populations.

Authors:  A Nádas; E I Goncharova; T G Rossman
Journal:  Mutat Res       Date:  1996-03-26       Impact factor: 2.433

10.  Modeling and measurement of the spontaneous mutation rate in mammalian cells.

Authors:  T G Rossman; E I Goncharova; A Nádas
Journal:  Mutat Res       Date:  1995-04       Impact factor: 2.433

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  1 in total

1.  Accumulation of neutral mutations in growing cell colonies with competition.

Authors:  Ron Sorace; Natalia L Komarova
Journal:  J Theor Biol       Date:  2012-08-23       Impact factor: 2.691

  1 in total

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