Sentence examples for multiple modulator genes from inspiring English sources

In the present study we aim to explore the joint effects of multiple modulator genes in modulating global gene regulation and dissect the biological functions in breast cancer.

Here we propose the Covariability-based Multiple Regression (CoMRe) method to model the relationships between multiple modulator genes and modulated gene-gene regulation in breast cancer.

In the present study, we presented the CoMRe algorithm for systematically investigating how multiple modulator genes jointly determine pairwise regulation strength of modulated genes.

Based on the covariability, we proposed a multiple regression model to study the relationship between multiple modulator genes and covariability of gene pair.

We generated a regression model that estimates the relationship between multiple modulator genes (assumed to be independent) and strengthen of regulation (i.e. correlation) between two modulated genes from the microarray dataset.

In this study, our objective is to extend the analysis to inferring multiple modulators co-modulated gene regulation, using a correlation-based regression approach.

Collectively, the present study is aimed to statistically infer the relationship between multiple modulators and modulated gene regulation and to study the associated biological functions in breast cancer.

In the present study we aim to statistically infer the relationship between multiple modulators and modulated gene regulation (illustration in Figure 1A) and dissect biological functions governed by it in breast cancer.

Among the 14,084,778 co-modulation patterns, regression p-values (significance of individual modulator genes in the multiple regression model) were roughly uniformly distributed.

Previous studies have demonstrated the involvement of genes modulated by single modulator genes in cancers, including breast cancer.

Therefore, CoMRe was designed to evaluate how co-variability of genome-wide gene pairs was dependent on modulator genes based on a multiple regression model; the analysis was focused on modulation, rather than direct or causal regulation, or co-regulation (i.e., regulated changes in gene expression levels).