Randomization Strategies Affect Motif Significance Analysis in TF-miRNA-Gene Regulatory Networks.
J Integr Bioinform
; 14(2)2017 Jul 04.
Article
en En
| MEDLINE
| ID: mdl-28675749
ABSTRACT
Gene-regulatory networks are an abstract way of capturing the regulatory connectivity between transcription factors, microRNAs, and target genes in biological cells. Here, we address the problem of identifying enriched co-regulatory three-node motifs that are found significantly more often in real network than in randomized networks. First, we compare two randomization strategies, that either only conserve the degree distribution of the nodes' in- and out-links, or that also conserve the degree distributions of different regulatory edge types. Then, we address the issue how convergence of randomization can be measured. We show that after at most 10 × |E| edge swappings, converged motif counts are obtained and the memory of initial edge identities is lost.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Factores de Transcripción
/
MicroARNs
/
Redes Reguladoras de Genes
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
J Integr Bioinform
Asunto de la revista:
INFORMATICA MEDICA
Año:
2017
Tipo del documento:
Article