CSI: a nonparametric Bayesian approach to network inference from multiple perturbed time series gene expression data.
Stat Appl Genet Mol Biol
; 14(3): 307-10, 2015 Jun.
Article
en En
| MEDLINE
| ID: mdl-26030796
ABSTRACT
Here we introduce the causal structure identification (CSI) package, a Gaussian process based approach to inferring gene regulatory networks (GRNs) from multiple time series data. The standard CSI approach infers a single GRN via joint learning from multiple time series datasets; the hierarchical approach (HCSI) infers a separate GRN for each dataset, albeit with the networks constrained to favor similar structures, allowing for the identification of context specific networks. The software is implemented in MATLAB and includes a graphical user interface (GUI) for user friendly inference. Finally the GUI can be connected to high performance computer clusters to facilitate analysis of large genomic datasets.
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1
Banco de datos:
MEDLINE
Asunto principal:
Programas Informáticos
/
Perfilación de la Expresión Génica
Idioma:
En
Año:
2015
Tipo del documento:
Article