ArticlePloS one2014
RNA graph partitioning for the discovery of RNA modularity: a novel application of graph partition algorithm to biology.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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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
17 citing papers in PubMed, 20 citations in OpenAlex.
- Viral RNAs as Dual Graphs: Extending the Motif Universe of RNAs.bioRxiv : the preprint server for biology · 2026Article
- Open questions on viral frameshifting: Exploiting the structural plasticity of the frameshifting element for therapeutic intervention.Biophysical journal · 2026Review
- How large is the universe of RNA-like motifs? A clustering analysis of RNA graph motifs using topological descriptors.PLoS computational biology · 2025Article
- Water-mediated ribonucleotide-amino acid pairs and higher-order structures at the RNA-protein interface: analysis of the crystal structure database and a topological classification.NAR genomics and bioinformatics · 2024Article
- RNA-As-Graphs Motif Atlas-Dual Graph Library of RNA Modules and Viral Frameshifting-Element Applications.International journal of molecular sciences · 2022Article
- A Fiedler Vector Scoring Approach for Novel RNA Motif Selection.The journal of physical chemistry. B · 2021Article
- Identification of novel RNA design candidates by clustering the extended RNA-As-Graphs library.Biochimica et biophysica acta. General subjects · 2020Article
- Inverse folding with RNA-As-Graphs produces a large pool of candidate sequences with target topologies.Journal of structural biology · 2020Article
- An extended dual graph library and partitioning algorithm applicable to pseudoknotted RNA structures.Methods (San Diego, Calif.) · 2019Article
- Going beyond base-pairs: topology-based characterization of base-multiplets in RNA.RNA (New York, N.Y.) · 2019Article
- A pipeline for computational design of novel RNA-like topologies.Nucleic acids research · 2018Article
- Dual Graph Partitioning Highlights a Small Group of Pseudoknot-Containing RNA Submotifs.Genes · 2018Article
- Adventures with RNA graphs.Methods (San Diego, Calif.) · 2018Review
- F-RAG: Generating Atomic Coordinates from RNA Graphs by Fragment Assembly.Journal of molecular biology · 2017Article
- Opportunities and Challenges in RNA Structural Modeling and Design.Biophysical journal · 2017Article
- Partitioning and Classification of RNA Secondary Structures into Pseudonotted and Pseudoknot-free Regions Using a Graph-Theoretical Approach.IAENG international journal of computer science · 2017Article
- Predicting Large RNA-Like Topologies by a Knowledge-Based Clustering Approach.Journal of molecular biology · 2016Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Graph representations have been widely used to analyze and design various economic, social, military, political, and biological networks. In systems biology, networks of cells and organs are useful for understanding disease and medical treatments and, in structural biology, structures of molecules can be described, including RNA structures. In our RNA-As-Graphs (RAG) framework, we represent RNA structures as tree graphs by translating unpaired regions into vertices and helices into edges. Here we explore the modularity of RNA structures by applying graph partitioning known in graph theory to divide an RNA graph into subgraphs. To our knowledge, this is the first application of graph partitioning to biology, and the results suggest a systematic approach for modular design in general. The graph partitioning algorithms utilize mathematical properties of the Laplacian eigenvector (µ2) corresponding to the second eigenvalues (λ2) associated with the topology matrix defining the graph: λ2 describes the overall topology, and the sum of µ2's components is zero. The three types of algorithms, termed median, sign, and gap cuts, divide a graph by determining nodes of cut by median, zero, and largest gap of µ2's components, respectively. We apply these algorithms to 45 graphs corresponding to all solved RNA structures up through 11 vertices (∼ 220 nucleotides). While we observe that the median cut divides a graph into two similar-sized subgraphs, the sign and gap cuts partition a graph into two topologically-distinct subgraphs. We find that the gap cut produces the best biologically-relevant partitioning for RNA because it divides RNAs at less stable connections while maintaining junctions intact. The iterative gap cuts suggest basic modules and assembly protocols to design large RNA structures. Our graph substructuring thus suggests a systematic approach to explore the modularity of biological networks. In our applications to RNA structures, subgraphs also suggest design strategies for novel RNA motifs.
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Registered trials
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.