We have developed new BN algorithms and tools for analysis of gene interaction networks using high
throughput gene expression data.
He group is also interested in high
throughput gene expression data analysis, especially using Bayesian network (BN) approaches.
Not exact matches
The overarching goal of his research is to utilize high -
throughput genomic
data sets, mostly based on DNA sequencing, in order to build models that explain how
gene expression is regulated.
Dr Gilchrist said: «This study suggests that we may improve significantly on the widely used analysis methods for determining
gene expression levels from high
throughput sequence
data: absolute quantitation offers a much sounder basis for determining changes in
gene expression level, a measure widely used to determine the consequence of genetic, chemical or physical disturbances in living systems.»
To enable comparison of
gene expression in diverse bacterial species in myriad sample types and growth conditions, much of his work is dedicated to developing more robust and high -
throughput methods for generating bacterial cDNA libraries and mining bacterial RNA - Seq
data for biologically relevant trends.
Provided
data analysis that included statistics package development with staff statisticians, and high
throughput assay advent and development (immediate early
gene expression); Taq - man primer - probe research and design using primer express.