The Local Edge Machine: inference of dynamic models of gene regulation.
Genome Biol
; 17(1): 214, 2016 10 19.
Article
em En
| MEDLINE
| ID: mdl-27760556
ABSTRACT
We present a novel approach, the Local Edge Machine, for the inference of regulatory interactions directly from time-series gene expression data. We demonstrate its performance, robustness, and scalability on in silico datasets with varying behaviors, sizes, and degrees of complexity. Moreover, we demonstrate its ability to incorporate biological prior information and make informative predictions on a well-characterized in vivo system using data from budding yeast that have been synchronized in the cell cycle. Finally, we use an atlas of transcription data in a mammalian circadian system to illustrate how the method can be used for discovery in the context of large complex networks.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Transcrição Gênica
/
Regulação da Expressão Gênica
/
Bases de Dados Genéticas
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Redes Reguladoras de Genes
Tipo de estudo:
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article