Identification of self‐regulatory network motifs in reverse engineering gene regulatory networks using microarray gene expression data
Gene Regulatory Networks (GRNs) are reconstructed from the microarray gene expression
data through diversified computational approaches. This process ensues in symmetric and …
data through diversified computational approaches. This process ensues in symmetric and …
Hybrid, logical and linear modelling to predict in silico the effect of perturbations on metabolism
S Le Bars - 2022 - theses.hal.science
Perturbations induced by disease, treatment or environmental stress affect living organisms
in various ways. Thus, the expression of certain genes will be impacted, affecting its …
in various ways. Thus, the expression of certain genes will be impacted, affecting its …
[图书][B] Development of dynamic Bayesian network for the analysis of high-dimensional biomedical data
A Akutekwe - 2017 - search.proquest.com
Inferring gene regulatory networks (GRNs) from time-course expression data is a major
challenge in Bioinformatics. Advances in microarray technology have given rise to cheap …
challenge in Bioinformatics. Advances in microarray technology have given rise to cheap …