Bayesian networks (BNs) provide a probabilistic, graphical framework for modeling high-dimensional joint distributions with complex correlation structures. BNs have wide applications in many disciplin

NIAID Data Ecosystem40

Partial correlations among the birth year, degree, importance, and expression level of yeast genes.

基因网络分析

酵母系统生物学

aBirth year is the year during which the gene was first included into the PPI (or GI) network. Degree is the number of interactions the gene has in the PPI (or GI) network in year-2007. Importance is

NIAID Data Ecosystem30

Evolutionary Engineering and Transcriptomic & Genomic Analysis of Phenylethanol-resistant Saccharomyces cerevisiae

微生物耐受性

酵母系统生物学

The aim of this study was to develop phenylethanol-resistant Saccharomyces cerevisiae mutants by using evolutionary engineering and to characterize the selected mutants at phenotypic, genomic and tran

NIAID Data Ecosystem40

FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks

生物网络推断

差异网络分析

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 m

NIAID Data Ecosystem40