Validation of a mathematical model of gene transcription in aggregated cellular systems: Application to L1 retrotransposition

Grzegorz A. Rempala, Kenneth S. Ramos, Ted Kalbfleisch, Ivo Teneng

Research output: Contribution to journalArticle

9 Scopus citations

Abstract

We present a methodology aimed at partial validation and accuracy-precision assessment of a mathematical model of gene transcription at the cellular level. The method is based on the analysis of time-series measurements aggregated over a large number of cells. Such measurements are typically obtained via reverse transcriptase-polymerase chain reaction (RT-PCR) experiments. The validation procedure presented herein uses as an example data on L1 retrotransposon gene in HeLa cells. The procedure compares model predicted values with the RT-PCR data for L1 by means of the standard Bayesian statistical techniques with the help of modern Markov-Chain Monte-Carlo methodology.

Original languageEnglish (US)
Pages (from-to)339-349
Number of pages11
JournalJournal of Computational Biology
Volume14
Issue number3
DOIs
StatePublished - Apr 1 2007
Externally publishedYes

Keywords

  • Aggregated data
  • Gene transcription model
  • L1 retrotransposon
  • Model validation
  • Posterior confidence bounds
  • RT-PCR
  • Reaction rate equation

ASJC Scopus subject areas

  • Modeling and Simulation
  • Molecular Biology
  • Genetics
  • Computational Mathematics
  • Computational Theory and Mathematics

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