ArticleFrontiers in plant science2015
CoExpNetViz: Comparative Co-Expression Networks Construction and Visualization Tool.
Article in Frontiers in plant science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses that pooled it.
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Who cites it
60 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Transcriptome meta-analysis of abiotic stresses-responsive genes and identification of candidate transcription factors for broad stress tolerance in wheat.Protoplasma · 2023Pooled it
- Meta-analysis of drought-tolerant genotypes in Oryza sativa: A network-based approach.PloS one · 2019Pooled it
- Transcriptomic insights into the biocontrol mechanism of Trichoderma spp. against Fusarium wilt in melon.Stress biology · 2026Article
- Constructing gene co-functional and co-regulatory networks from public transcriptomes using condition-specific ensemble co-expression.Nature communications · 2026Article
- Hormone-centric multi-omics atlas of flower and early fruit development in tomato.Plant communications · 2026Article
- Complex engineering of Solanum alkaloids structural diversity in Nicotiana benthamiana.Plant biotechnology journal · 2026Article
- Functions and Synthesis of Abscisic Acid (ABA) in Humans-Insights from Computational Approaches.International journal of molecular sciences · 2025Review
- Developmental system drift and modular gene regulatory networks shape gastrulation inLife science alliance · 2025Article
- Deciphering the role of monoacylglycerol lipases (MAGL) under abiotic stress and lipid metabolism in soybean (Glycine max L.).Plant biotechnology journal · 2025Article
- Diurnal rhythms in durum wheat triggered by Rhopalosiphum padi (bird cherry-oat aphid).BMC plant biology · 2025Article
- Transcriptome analyses revealPhysiology and molecular biology of plants : an international journal of functional plant biology · 2025Article
- Navigating the challenges of engineering composite specialized metabolite pathways in plants.The Plant journal : for cell and molecular biology · 2025Review
- ACT2.6: Global Gene Coexpression Network inGenes · 2025Article
- A MYB transcription factor underlying plant height in sorghum qHT7.1 and maize Brachytic 1 loci.The Plant journal : for cell and molecular biology · 2024Article
- Force-triggered density gradient sedimentation and cocktail enzyme digestion treatment for isolation of single dermal papilla cells from follicular unit extraction harvesting human hair follicles.Stem cell research & therapy · 2024Article
- Genome-Wide Analysis ofPlants (Basel, Switzerland) · 2024Article
- Trehalase inhibition inJournal of biosciences · 2024Article
- Causes and consequences of endogenous hypoxia on growth and metabolism of developing maize kernels.Plant physiology · 2023Article
- Transcriptome changes induced by Arbuscular mycorrhizal symbiosis in leaves of durum wheat (Triticum durum Desf.) promote higher salt tolerance.Scientific reports · 2023Article
- The tomato cytochrome P450 CYP712G1 catalyses the double oxidation of orobanchol en route to the rhizosphere signalling strigolactone, solanacol.The New phytologist · 2022Article
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6 authors.
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Abstract
motivationComparative transcriptomics is a common approach in functional gene discovery efforts. It allows for finding conserved co-expression patterns between orthologous genes in closely related plant species, suggesting that these genes potentially share similar function and regulation. Several efficient co-expression-based tools have been commonly used in plant research but most of these pipelines are limited to data from model systems, which greatly limit their utility. Moreover, in addition, none of the existing pipelines allow plant researchers to make use of their own unpublished gene expression data for performing a comparative co-expression analysis and generate multi-species co-expression networks.
resultsWe introduce CoExpNetViz, a computational tool that uses a set of query or "bait" genes as an input (chosen by the user) and a minimum of one pre-processed gene expression dataset. The CoExpNetViz algorithm proceeds in three main steps; (i) for every bait gene submitted, co-expression values are calculated using mutual information and Pearson correlation coefficients, (ii) non-bait (or target) genes are grouped based on cross-species orthology, and (iii) output files are generated and results can be visualized as network graphs in Cytoscape. AVAILABILITY: The CoExpNetViz tool is freely available both as a PHP web server (link: http://bioinformatics.psb.ugent.be/webtools/coexpr/) (implemented in C++) and as a Cytoscape plugin (implemented in Java). Both versions of the CoExpNetViz tool support LINUX and Windows platforms.
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