Reconstruction of transcriptional dynamics from gene reporter data using differential equations.

ABSTRACT:

Motivation

Promoter-driven reporter genes, notably luciferase and green fluorescent protein, provide a tool for the generation of a vast array of time-course data sets from living cells and organisms. The aim of this study is to introduce a modeling framework based on stochastic differential equations (SDEs) and ordinary differential equations (ODEs) that addresses the problem of reconstructing transcription time-course profiles and associated degradation rates. The dynamical model is embedded into a Bayesian framework and inference is performed using Markov chain Monte Carlo algorithms.

Results

We present three case studies where the methodology is used to reconstruct unobserved transcription profiles and to estimate associated degradation rates. We discuss advantages and l

SUBMITTER: Finkenstadt B 

PROVIDER: S-EPMC2639297 | biostudies-literature | 2008 Dec

REPOSITORIES: biostudies-literature