Ranking genome-wide correlation measurements improves microarray and RNA-seq based global and targeted co-expression networks
F Liesecke, D Daudu, R Dugé de Bernonville… - Scientific reports, 2018 - nature.com
Co-expression networks are essential tools to infer biological associations between gene
products and predict gene annotation. Global networks can be analyzed at the transcriptome …
products and predict gene annotation. Global networks can be analyzed at the transcriptome …
Comparative study of RNA-seq- and Microarray-derived coexpression networks in Arabidopsis thaliana
Motivation: Coexpression networks are data-derived representations of genes behaving in a
similar way across tissues and experimental conditions. They have been used for …
similar way across tissues and experimental conditions. They have been used for …
Improved gene co-expression network quality through expression dataset down-sampling and network aggregation
Large-scale gene co-expression networks are an effective methodology to analyze sets of
co-expressed genes and discover new gene functions or associations. Distances between …
co-expressed genes and discover new gene functions or associations. Distances between …
Comparison of co-expression measures: mutual information, correlation, and model based indices
L Song, P Langfelder, S Horvath - BMC bioinformatics, 2012 - Springer
Background Co-expression measures are often used to define networks among genes.
Mutual information (MI) is often used as a generalized correlation measure. It is not clear …
Mutual information (MI) is often used as a generalized correlation measure. It is not clear …
Maximizing capture of gene co-expression relationships through pre-clustering of input expression samples: an Arabidopsis case study
Background In genomics, highly relevant gene interaction (co-expression) networks have
been constructed by finding significant pair-wise correlations between genes in expression …
been constructed by finding significant pair-wise correlations between genes in expression …
Canonical correlation analysis for RNA-seq co-expression networks
Digital transcriptome analysis by next-generation sequencing discovers substantial mRNA
variants. Variation in gene expression underlies many biological processes and holds a key …
variants. Variation in gene expression underlies many biological processes and holds a key …
Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size
Background Co-expression has been widely used to identify novel regulatory relationships
using high throughput measurements, such as microarray and RNA-seq data. Evaluation …
using high throughput measurements, such as microarray and RNA-seq data. Evaluation …
Distance correlation application to gene co-expression network analysis
Background To construct gene co-expression networks, it is necessary to evaluate the
correlation between different gene expression profiles. However, commonly used correlation …
correlation between different gene expression profiles. However, commonly used correlation …
Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets
The meta-analysis of large-scale postgenomics data sets within public databases promises
to provide important novel biological knowledge. Statistical approaches including correlation …
to provide important novel biological knowledge. Statistical approaches including correlation …
Co-expression networks for plant biology: why and how
X Rao, RA Dixon - Acta biochimica et biophysica Sinica, 2019 - academic.oup.com
Co-expression network analysis is one of the most powerful approaches for interpretation of
large transcriptomic datasets. It enables characterization of modules of co-expressed genes …
large transcriptomic datasets. It enables characterization of modules of co-expressed genes …