Post-menopausal osteoporosis is one of the most common bone diseases in women. The aim of the present study was to predict the diagnostic function modules from a differential co-expression gene network in order to enhance the current understanding of the biological processes and to promote the early prevention and intervention of post-menopausal osteoporosis. The diagnostic function modules wer...

Association studies are widely utilized to analyze complex traits but their ability to disclose genetic architectures is often limited by statistical constraints, and functional insights are usually minimal in nonmodel organisms like forest trees. We developed an approach to integrate association mapping results with co-expression networks. We tested single nucleotide polymorphisms (SNPs) in 26...

We improve the reliability of detecting coexpressed gene pairs from microarray data by introducing a novel probe-level quality-weighted similarity measure for combining data across different Affymetrix experiments. In construction of gene coexpression networks, the proposed procedure is less sensitive to noise than the corresponding single-experiment approaches or the conventional integrative a...

From merging a number of data sources, we created an extensive map of the transcriptional regulatory network in yeast, comprising 7419 interactions connecting 180 transcription factors (TFs) with their target genes. We integrated this network with gene-expression data, relating the expression profiles of TFs and target genes. We found that genes targeted by the same TF tend to be co-expressed, ...

Accumulated transcriptome data can be used to investigate regulatory networks of genes involved in various biological systems. Co-expression analysis data sets generated from comprehensively collected transcriptome data sets now represent efficient resources that are capable of facilitating the discovery of genes with closely correlated expression patterns. In order to construct a co-expression...

Plants are fascinating and complex organisms. A comprehensive understanding of the organization, function and evolution of plant genes is essential to disentangle important biological processes and to advance crop engineering and breeding strategies. The ultimate aim in deciphering complex biological processes is the discovery of causal genes and regulatory mechanisms controlling these processe...

MOTIVATION RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks. RESULTS We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are as...

MicroRNAs, a new class of key regulators of gene expression, have been shown to be involved in diverse biological processes and linked to many human diseases. To elucidate miRNA function from a global perspective, we constructed a conserved miRNA co-expression network by integrating multiple human and mouse miRNA expression data. We found that these conserved co-expressed miRNA pairs tend to re...

Exploring biological systems from highly complex datasets is an important task for systems biology. The present study examined co-expression dynamics of mouse heart transcriptome by spectral graph clustering (SGC) to identify a heart transcriptomic network. SGC of microarray data produced 17 classified biological conditions (called condition spectrum, CS) and co-expression patterns by generatin...

this paper aims to study the performance of the international journal of information science and management (ijism) over a decade using scientometric approach. it also tries to study the                     co-authorship network of authors and institutions using different macro- and micro-level social network analysis metrics. a total of 173 articles published in 23 issues of the ijism covering...