Overview and Evaluation of Recent Methods for Statistical Inference of Gene Regulatory Networks from Time Series Data.
Methods Mol Biol
; 1883: 49-94, 2019.
Article
em En
| MEDLINE
| ID: mdl-30547396
ABSTRACT
A challenging problem in systems biology is the reconstruction of gene regulatory networks from postgenomic data. A variety of reverse engineering methods from machine learning and computational statistics have been proposed in the literature. However, deciding on the best method to adopt for a particular application or data set might be a confusing task. The present chapter provides a broad overview of state-of-the-art methods with an emphasis on conceptual understanding rather than a deluge of mathematical details, and the pros and cons of the various approaches are discussed. Guidance on practical applications with pointers to publicly available software implementations are included. The chapter concludes with a comprehensive comparative benchmark study on simulated data and a real-work application taken from the current plant systems biology.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Biologia de Sistemas
/
Redes Reguladoras de Genes
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Ciência de Dados
/
Modelos Genéticos
Tipo de estudo:
Guideline
/
Prognostic_studies
Idioma:
En
Revista:
Methods Mol Biol
Ano de publicação:
2019
Tipo de documento:
Article