Published December 1, 2022
| Version v1
Publication
Learning Robust Dynamic Networks in Prokaryotes by Gene Expression Networks Iterative Explorer (GENIE)
Description
Genetic and genomic approaches have been used successfully to assign
genes to distinct regulatory networks, but the uncertainty concerning the connec tions between genes, the ambiguity inherent to the biological processes, and the
impossibility of experimentally determining the underlying biological properties
only allow a rough prediction of the dynamics of genes. Here we describe the GE NIE methodology that formulates alternative models of genetic regulatory networks
based on the available literature and transcription factor binding site evidence. It
also provides a framework for the analysis of these models optimized by genetic
algorithms, inferring their optimal parameters, simulating their behavior, evaluat ing them by integrating robustness, realness and flexibility criteria, and contrasting
the predictions to experimentally results obtained by Gene Fluorescence Protein
analysis. The application of this method to the regulatory network of the bacterium
Salmonella enterica uncovered new mechanisms that enable the inter-connection of
the PhoP/PhoQ and the PmrA/PmrB two component systems. The predictions were
experimentally verified to establish that both transcriptional and post-transcriptional
mechanisms are employed to connect these two systems.
Abstract
Ministerio de Ciencia y Tecnología BIO2004-0270-EAdditional details
Identifiers
- URL
- https://idus.us.es/handle//11441/139991
- URN
- urn:oai:idus.us.es:11441/139991