ArticleCell systems2017
Inference and Evolutionary Analysis of Genome-Scale Regulatory Networks in Large Phylogenies.
Article in Cell systems, 2017. 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.
- Wiring Between Close Nodes in Molecular Networks Evolves More Quickly Than Between Distant Nodes.Molecular biology and evolution · 2024Article
- Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets.Nature communications · 2023Article
- Dynamic regulatory module networks for inference of cell type-specific transcriptional networks.Genome research · 2022Article
- Enabling Studies of Genome-Scale Regulatory Network Evolution in Large Phylogenies with MRTLE.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Bayesian information sharing enhances detection of regulatory associations in rare cell types.Bioinformatics (Oxford, England) · 2021Article
- Evolution of regulatory networks associated with traits under selection in cichlids.Genome biology · 2021Article
- Comparative Analyses of Gene Co-expression Networks: Implementations and Applications in the Study of Evolution.Frontiers in genetics · 2021Review
- Gene Regulatory Networks ofFrontiers in microbiology · 2020Article
- Ancestral reconstruction of protein interaction networks.PLoS computational biology · 2019Article
- Global Transcriptional Programs in Archaea Share Features with the Eukaryotic Environmental Stress Response.Journal of molecular biology · 2019Review
- Inferring Regulatory Programs Governing Region Specificity of Neuroepithelial Stem Cells during Early Hindbrain and Spinal Cord Development.Cell systems · 2019Article
- Article
- Multi-study inference of regulatory networks for more accurate models of gene regulation.PLoS computational biology · 2019Article
- Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human.Methods in molecular biology (Clifton, N.J.) · 2019Article
- Towards a Dynamic Interaction Network of Life to unify and expand the evolutionary theory.BMC biology · 2018Review
- Comparative Transcriptomics Highlights New Features of the Iron Starvation Response in the Human PathogenFrontiers in microbiology · 2018Article
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11 authors.
Funding
Abstract
Changes in transcriptional regulatory networks can significantly contribute to species evolution and adaptation. However, identification of genome-scale regulatory networks is an open challenge, especially in non-model organisms. Here, we introduce multi-species regulatory network learning (MRTLE), a computational approach that uses phylogenetic structure, sequence-specific motifs, and transcriptomic data, to infer the regulatory networks in different species. Using simulated data from known networks and transcriptomic data from six divergent yeasts, we demonstrate that MRTLE predicts networks with greater accuracy than existing methods because it incorporates phylogenetic information. We used MRTLE to infer the structure of the transcriptional networks that control the osmotic stress responses of divergent, non-model yeast species and then validated our predictions experimentally. Interrogating these networks reveals that gene duplication promotes network divergence across evolution. Taken together, our approach facilitates study of regulatory network evolutionary dynamics across multiple poorly studied species.
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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 Socratic graph.