The CDE-score is derived by discretizing microarray data to identify significant gene expression changes. The usefulness of this method is demonstrated using a ...
Abstract— One of the goals of genomic expression analysis is to construct gene interaction networks from microarray data. Time course microarray data is a ...
Sep 22, 2015 · This study presents a revision of the current state-of-the-art discretization techniques, together with the key subjects that need to be considered.
Robust gene coexpression networks using signed distance correlation
www.ncbi.nlm.nih.gov › PMC8557847
We introduce the concept of signed distance correlation as a measure of dependency between two variables, and apply it to generate gene coexpression networks.
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Correlated Discretized Expression Score: A Method for Identifying ...
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Objective: We constructed a network-based method based on gene expression data in order to identify functional (or disease-relevant) modules. Method: We used ...
May 28, 2014 · We propose an expression pattern based method called GeCON to extract Ge ne CO-expression N etwork from microarray data. Pair-wise supports are ...
Here we only briefly describe the types of expression data and analysis methods used for gene network inference. Microarray experiments for our purposes can be ...
After giving some illustrations of the model, we study the problem of the reverse engineering of such networks, i.e., how to construct a network from gene ...
2006: Correlated Discretized Expression score: a method for identifying gene interaction networks from time course microarray expression data Conference ...
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Results: In this work, we present a novel method for inferring GRNs from gene expression data considering the non-linear dependence and topological structure of ...
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