Sentence examples for mutual information correlation from inspiring English sources

Song, L., Langfelder, P. & Horvath, S. Comparison of co-expression measures: mutual information, correlation, and model based indices.

We carry out experiments on mRMR, MBF and FCBF filters with three different metrics (mutual information, correlation coefficient and diff-criterion) using three binary data sets and four widely used classifiers.

Based on the definitions and concepts illustrated in the methodology part, we calculated the mutual information, correlation and P-values among pairwise genes for constructing regulatory activities.

Several methods have been proposed in literature [ 44], such as TIGRESS and Lasso based on linear regression, Aracne and CLR based on mutual information, correlation, and Bayesian networks.

Network inference methods can be split into five categories based on the underlying model in each case: regression, mutual information, correlation, Boolean regulatory networks, and other techniques [ 152].

A variety of gene network reconstruction methods based on gene expression data have been developed, e.g., regression, mutual information, correlation Bayesian network, meta predicators, and others (Marbach et al. 2012).

To uncover the orchestrated gene expressions guiding cell fate decision, we used Pearson (linear) correlation and mutual information (nonlinear correlation) metrics to investigate the collective dynamics of gene expressions for each stimulus.

We use the following relevance measures: mutual information, Pearson correlation coefficient r, Spearman rank correlation coefficient r S, and robust correlation coefficients rLWS A, rLWSLD, and rLWSLog (Definition 5).

Dysregulated interactions were defined as those exhibiting mutual information (essentially, correlation) in all samples except for a particular phenotype (loss-of-correlation) or lack of mutual information in all samples except for a particular phenotype (gain-of-correlation).

Instead of mutual information, generalized correlation coefficient (GCC) is adopted to measure D and R from Eqs. (1) to (5) for preserving predictability.

Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types.