ArticlePeerJ2014
Construction and comparison of gene co-expression networks shows complex plant immune responses.
Article in PeerJ, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 27 citations in OpenAlex.
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- Identification of the Transcriptional Regulatory Role of RUNX2 by Network Analysis in Lung Cancer Cells.Biomedicines · 2022Article
- Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom.Plants (Basel, Switzerland) · 2022Review
- Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis.Biology · 2022Article
- Approaches in Gene Coexpression Analysis in Eukaryotes.Biology · 2022Review
- Identifying large-scale interaction atlases using probabilistic graphs and external knowledge.Journal of clinical and translational science · 2022Article
- Juxtapose: a gene-embedding approach for comparing co-expression networks.BMC bioinformatics · 2021Article
- Reciprocal Changes in miRNA Expression with Pigmentation and Decreased Proliferation Induced in Mouse B16F1 Melanoma Cells by L-Tyrosine and 5-Bromo-2'-Deoxyuridine.International journal of molecular sciences · 2021Article
- X-Module: A novel fusion measure to associate co-expressed gene modules from condition-specific expression profiles.Journal of biosciences · 2020Article
- QTL mapping for maize starch content and candidate gene prediction combined with co-expression network analysis.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases.Frontiers in genetics · 2019Article
- Gene Coexpression Network Comparison via Persistent Homology.International journal of genomics · 2018Article
- THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease.Scientific reports · 2016Article
- Differential Coexpression Analysis Reveals Extensive Rewiring of Arabidopsis Gene Coexpression in Response to Pseudomonas syringae Infection.Scientific reports · 2016Article
- Learning from Co-expression Networks: Possibilities and Challenges.Frontiers in plant science · 2016Review
- A comparison of human and mouse gene co-expression networks reveals conservation and divergence at the tissue, pathway and disease levels.BMC evolutionary biology · 2015Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gene co-expression networks (GCNs) are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA). Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.