Simulated maximum likelihood method for estimating kinetic rates in gene expression

Tianhai Tian, Songlin Xu, Junbin Gao, Kevin Burrage

    Research output: Contribution to journalArticlepeer-review

    81 Citations (Scopus)

    Abstract

    Kinetic rate in gene expression is a key measurement of the stability of gene products and gives important information for the reconstruction of genetic regulatory networks. Recent developments in experimental technologies have made it possible to measure the numbers of transcripts and protein molecules in single cells. Although estimation methods based on deterministic models have been proposed aimed at evaluating kinetic rates from experimental observations, these methods cannot tackle noise in gene expression that may arise from discrete processes of gene expression, small numbers of mRNA transcript, fluctuations in the activity of transcriptional factors and variability in the experimental environment.
    Original languageEnglish
    Pages (from-to)84-91
    Number of pages8
    JournalBioinformatics
    Volume23
    Issue number1
    DOIs
    Publication statusPublished - 2007

    Fingerprint

    Dive into the research topics of 'Simulated maximum likelihood method for estimating kinetic rates in gene expression'. Together they form a unique fingerprint.

    Cite this