Cargando…
FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks
Biological networks provide additional information for the analysis of human diseases, beyond the traditional analysis that focuses on single variables. Gaussian graphical model (GGM), a probability model that characterizes the conditional dependence structure of a set of random variables by a graph...
Autores principales: | Wang, Ting, Ren, Zhao, Ding, Ying, Fang, Zhou, Sun, Zhe, MacDonald, Matthew L., Sweet, Robert A., Wang, Jieru, Chen, Wei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4752261/ https://www.ncbi.nlm.nih.gov/pubmed/26872036 http://dx.doi.org/10.1371/journal.pcbi.1004755 |
Ejemplares similares
-
Fast Bayesian inference in large Gaussian graphical models
por: Leday, Gwenaël G. R., et al.
Publicado: (2019) -
Memorandum: improvements of the GGM-EMI facility
por: CERN. Geneva. SPS Experiments Committee
Publicado: (1978) -
Bottom-up GGM algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways or processes
por: Kumari, Sapna, et al.
Publicado: (2016) -
Cancer Genetic Network Inference Using Gaussian Graphical
Models
por: Zhao, Haitao, et al.
Publicado: (2019) -
A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model
por: He, Hao, et al.
Publicado: (2019)