ArticleScientific reports2022
Hypergraph geometry reflects higher-order dynamics in protein interaction networks.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 57 citations in OpenAlex.
- Graph and Hypergraph Theories Applied to Dynamic Protein-Protein Interaction Network Analysis, and Deep-Learning Frameworks for Protein Complex Network Prediction.International journal of molecular sciences · 2026Review
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- Enriched knowledge representation in biological fields: a case study of literature-based discovery in Alzheimer's disease.Journal of biomedical semantics · 2025Article
- Network Geometry of Borsa Istanbul: Analyzing Sectoral Dynamics with Forman-Ricci Curvature.Entropy (Basel, Switzerland) · 2025Article
- Multi-source biological knowledge-guided hypergraph spatiotemporal subnetwork embedding for protein complex identification.Briefings in bioinformatics · 2024Article
- Functional Hypergraphs of Stock Markets.Entropy (Basel, Switzerland) · 2024Article
- A novel hierarchical network-based approach to unveil the complexity of functional microbial genome.BMC genomics · 2024Article
- Integration of protein sequence and protein-protein interaction data by hypergraph learning to identify novel protein complexes.Briefings in bioinformatics · 2024Article
- Topological and geometric analysis of cell states in single-cell transcriptomic data.Briefings in bioinformatics · 2024Article
- Charting cellular differentiation trajectories with Ricci flow.Nature communications · 2024Article
- Multi-scale geometric network analysis identifies melanoma immunotherapy response gene modules.Scientific reports · 2024Article
- The simpliciality of higher-order networks.EPJ data science · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- Multi-Scale Geometric Network Analysis Identifies Melanoma Immunotherapy Response Gene Modules.bioRxiv : the preprint server for biology · 2023Article
- PWN: enhanced random walk on a warped network for disease target prioritization.BMC bioinformatics · 2023Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Protein interactions form a complex dynamic molecular system that shapes cell phenotype and function; in this regard, network analysis is a powerful tool for studying the dynamics of cellular processes. Current models of protein interaction networks are limited in that the standard graph model can only represent pairwise relationships. Higher-order interactions are well-characterized in biology, including protein complex formation and feedback or feedforward loops. These higher-order relationships are better represented by a hypergraph as a generalized network model. Here, we present an approach to analyzing dynamic gene expression data using a hypergraph model and quantify network heterogeneity via Forman-Ricci curvature. We observe, on a global level, increased network curvature in pluripotent stem cells and cancer cells. Further, we use local curvature to conduct pathway analysis in a melanoma dataset, finding increased curvature in several oncogenic pathways and decreased curvature in tumor suppressor pathways. We compare this approach to a graph-based model and a differential gene expression approach.
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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.