This paper focuses on a simple method for
finding out the set of genes which have very significant
contribution in case of ‘Burkholderia Pseudomalli’ for its
growth and then find out the genetic network formed by
them. Computation for this purpose has been carried out
using Microarray gene expression time series dataset of
‘Burkholderia Pseudomalli’ bacteria at its various
phases of growth. The dataset has been obtained from
GEO data base of NCBI website. This Microarray data
set represents the external manifestation of internal
genetic activity resulting into genetic network. From the
5289 by 47 genetic time series data, efforts were made to
detect the responsible gene set which has actively
participated in the growth activity of the bacteria and the
genetic network thereof. Here, ‘fidelity matrix’ approach
has been adopted to reduce dataset by detecting the most
responsible gene for the purpose. From this set of
responsible gene sets a suitable genetic network searched
using Artificial Neural Network (ANN). Out of the many
possible genetic networks derived from running ANN
several times, only the network, common to all the
obtained networks, is chosen. Once the responsible gene
set along with its network is determined, it can lead to
further investigations on metabolic pathway engineering,
drug discovery etc.
