Literature DB >> 18805994

Estimating single-cell lag times via a Bayesian scheme.

P K Malakar1, G C Barker.   

Abstract

Network models offer computationally efficient tools for estimating the variability of single-cell lag phases. Currently, optical methods for estimating the variability of single-cell lag phases use single-cell inocula and are technically challenging. A Bayesian network model incorporating small uncertain inocula addresses these limitations.

Mesh：

Year:  2008        PMID： 18805994      PMCID： PMC2583504          DOI： 10.1128/AEM.01277-08

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN： 0099-2240            Impact factor:   4.792


  5 in total

1.  Heterogeneity of times required for germination and outgrowth from single spores of nonproteolytic Clostridium botulinum.

Authors:  Sandra C Stringer; Martin D Webb; Susan M George; Carmen Pin; Michael W Peck
Journal:  Appl Environ Microbiol       Date:  2005-09       Impact factor: 4.792

2.  Comparison of Stochastic and Deterministic Concepts of Bacterial Lag.

Authors: 
Journal:  J Theor Biol       Date:  1998-06-07       Impact factor: 2.691

3.  Estimating bacterial growth parameters by means of detection times.

Authors:  J Baranyi; C Pin
Journal:  Appl Environ Microbiol       Date:  1999-02       Impact factor: 4.792

4.  A comparison of the bioscreen method and microscopy for the determination of lag times of individual cells of listeria monocytogenes.

Authors:  Y Wu; M W Griffiths; R C McKellar
Journal:  Lett Appl Microbiol       Date:  2000-06       Impact factor: 2.858

5.  Effect of environmental parameters (temperature, pH and a(w)) on the individual cell lag phase and generation time of Listeria monocytogenes.

Authors:  K Francois; F Devlieghere; A R Standaert; A H Geeraerd; J F Van Impe; J Debevere
Journal:  Int J Food Microbiol       Date:  2006-02-20       Impact factor: 5.277
  5 in total
  1 in total

1.  Estimating risk from small inocula by using population growth parameters.

Authors:  P K Malakar; G C Barker
Journal:  Appl Environ Microbiol       Date:  2009-07-31       Impact factor: 4.792
  1 in total

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