Comparative analyses of gene co-expression networks: Implementations and applications in the study of evolution
Similarities and differences in the associations of biological entities among species can
provide us with a better understanding of evolutionary relationships. Often the evolution of …
provide us with a better understanding of evolutionary relationships. Often the evolution of …
[HTML][HTML] Network-based approaches for modeling disease regulation and progression
Molecular interaction networks lay the foundation for studying how biological functions are
controlled by the complex interplay of genes and proteins. Investigating perturbed processes …
controlled by the complex interplay of genes and proteins. Investigating perturbed processes …
Gene co-expression analysis for functional classification and gene–disease predictions
Gene co-expression networks can be used to associate genes of unknown function with
biological processes, to prioritize candidate disease genes or to discern transcriptional …
biological processes, to prioritize candidate disease genes or to discern transcriptional …
CEMiTool: a Bioconductor package for performing comprehensive modular co-expression analyses
Background The analysis of modular gene co-expression networks is a well-established
method commonly used for discovering the systems-level functionality of genes. In addition …
method commonly used for discovering the systems-level functionality of genes. In addition …
Natural history–guided omics reveals plant defensive chemistry against leafhopper pests
Although much is known about plant traits that function in nonhost resistance against
pathogens, little is known about nonhost resistance against herbivores, despite its …
pathogens, little is known about nonhost resistance against herbivores, despite its …
DGCA: a comprehensive R package for differential gene correlation analysis
Background Dissecting the regulatory relationships between genes is a critical step towards
building accurate predictive models of biological systems. A powerful approach towards this …
building accurate predictive models of biological systems. A powerful approach towards this …
Improved biomarker discovery through a plot twist in transcriptomic data analysis
Background Transcriptomic analysis is crucial for understanding the functional elements of
the genome, with the classic method consisting of screening transcriptomics datasets for …
the genome, with the classic method consisting of screening transcriptomics datasets for …
Dissection of regulatory networks that are altered in disease via differential co-expression
Comparing the gene-expression profiles of sick and healthy individuals can help in
understanding disease. Such differential expression analysis is a well-established way to …
understanding disease. Such differential expression analysis is a well-established way to …
[HTML][HTML] DiffCorr: an R package to analyze and visualize differential correlations in biological networks
A Fukushima - Gene, 2013 - Elsevier
Large-scale “omics” data, such as microarrays, can be used to infer underlying cellular
regulatory networks in organisms, enabling us to better understand the molecular basis of …
regulatory networks in organisms, enabling us to better understand the molecular basis of …
Host transcriptional response to influenza and other acute respiratory viral infections–a prospective cohort study
Y Zhai, LM Franco, RL Atmar, JM Quarles… - PLoS …, 2015 - journals.plos.org
To better understand the systemic response to naturally acquired acute respiratory viral
infections, we prospectively enrolled 1610 healthy adults in 2009 and 2010. Of these, 142 …
infections, we prospectively enrolled 1610 healthy adults in 2009 and 2010. Of these, 142 …