ArticleScientific reports2016
Analysis of the dynamic co-expression network of heart regeneration in the zebrafish.
Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Whole body regeneration deploys a rewired embryonic gene regulatory network logic.Nature communications · 2025Article
- Aggregation of recount3 RNA-seq data improves inference of consensus and tissue-specific gene coexpression networks.Genome research · 2025Article
- The Hazards of Regeneration: From Morgan's Legacy to Evo-Devo.Methods in molecular biology (Clifton, N.J.) · 2022Review
- Gene co-expression network analysis in zebrafish reveals chemical class specific modules.BMC genomics · 2021Article
- The transcriptome of anterior regeneration in earthworm Eudrilus eugeniae.Molecular biology reports · 2021Article
- Cardiac Regeneration and Tumor Growth-What Do They Have in Common?Frontiers in genetics · 2020Article
- Understanding the Metabolic Profile of Macrophages During the Regenerative Process in Zebrafish.Frontiers in physiology · 2019Article
- Delineating the Dynamic Transcriptome Response of mRNA and microRNA during Zebrafish Heart Regeneration.Biomolecules · 2018Article
- Damage-responsive elements inGenome research · 2018Article
- Gene co-expression analysis for functional classification and gene-disease predictions.Briefings in bioinformatics · 2018Article
- Genomics and Epigenomics of Congenital Heart Defects: Expert Review and Lessons Learned in Africa.Omics : a journal of integrative biology · 2018Review
- Transient fibrosis resolves via fibroblast inactivation in the regenerating zebrafish heart.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Hub genes in a pan-cancer co-expression network show potential for predicting drug responses.F1000Research · 2018Article
- Temporally distinct transcriptional regulation of myocyte dedifferentiation and Myofiber growth during muscle regeneration.BMC genomics · 2017Article
- Exploring Wound-Healing Genomic Machinery with a Network-Based Approach.Pharmaceuticals (Basel, Switzerland) · 2017Article
- Zebrafish heart regeneration: 15 years of discoveries.Regeneration (Oxford, England) · 2017Review
- More than Just a Simple Cardiac Envelope; Cellular Contributions of the Epicardium.Frontiers in cell and developmental biology · 2017Review
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The zebrafish has the capacity to regenerate its heart after severe injury. While the function of a few genes during this process has been studied, we are far from fully understanding how genes interact to coordinate heart regeneration. To enable systematic insights into this phenomenon, we generated and integrated a dynamic co-expression network of heart regeneration in the zebrafish and linked systems-level properties to the underlying molecular events. Across multiple post-injury time points, the network displays topological attributes of biological relevance. We show that regeneration steps are mediated by modules of transcriptionally coordinated genes, and by genes acting as network hubs. We also established direct associations between hubs and validated drivers of heart regeneration with murine and human orthologs. The resulting models and interactive analysis tools are available at http://infused.vital-it.ch. Using a worked example, we demonstrate the usefulness of this unique open resource for hypothesis generation and in silico screening for genes involved in heart regeneration.
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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.