Multiscale Modeling of Cross-Regulatory Transcript and Protein Influences.
Methods Mol Biol
; 2328: 115-138, 2021.
Article
en En
| MEDLINE
| ID: mdl-34251622
ABSTRACT
With the popularity of high-throughput transcriptomic techniques like RNAseq, models of gene regulatory networks have been important tools for understanding how genes are regulated. These transcriptomic datasets are usually assumed to reflect their associated proteins. This assumption, however, ignores post-transcriptional, translational, and post-translational regulatory mechanisms that regulate protein abundance but not transcript abundance. Here we describe a method to model cross-regulatory influences between the transcripts and proteins of a set of genes using abundance data collected from a series of transgenic experiments. The developed model can capture the effects of regulation that impacts transcription as well as regulatory mechanisms occurring after transcription. This approach uses a sparse maximum likelihood algorithm to determine relationships that influence transcript and protein abundance. An example of how to explore the network topology of this type of model is also presented. This model can be used to predict how the transcript and protein abundances will change in novel transgenic modification strategies.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Proteínas
/
Regulación de la Expresión Génica
/
Perfilación de la Expresión Génica
/
Proteómica
/
Redes Reguladoras de Genes
/
Metabolómica
/
Transcriptoma
Tipo de estudio:
Prognostic_studies
Idioma:
En
Revista:
Methods Mol Biol
Asunto de la revista:
BIOLOGIA MOLECULAR
Año:
2021
Tipo del documento:
Article
País de afiliación:
Estados Unidos