ArticleNPJ systems biology and applications2019
The multiplex network of human diseases.
Article in NPJ systems biology and applications, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed.
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- Modeling roles and trade-offs in multiplex networks.Nature communications · 2026Article
- A complex network perspective on brain disease.Biological reviews of the Cambridge Philosophical Society · 2026Review
- Multilayer network approaches to omics data integration in digital twins for cancer research.Frontiers in systems biology · 2026Review
- Transcriptional regulatory network analysis uncovers modular gene control and potential key regulators in diabetic cardiomyopathy.Frontiers in cell and developmental biology · 2026Article
- Unraveling the Network Signatures of Oncogenicity in Virus-Human Protein-Protein Interactions.Entropy (Basel, Switzerland) · 2025Article
- Disease clusters and their genetic determinants following a diagnosis of depression: analyses based on a novel three-dimensional disease network approach.Molecular psychiatry · 2025Article
- Challenges and opportunities for digital twins in precision medicine from a complex systems perspective.NPJ digital medicine · 2025Review
- Precision cardiovascular medicine: shifting the innovation paradigm.Frontiers in science · 2025Article
- Combining multifaceted aspects of technology innovations through fuzzy clustering of multilayer networks.PloS one · 2025Article
- Disease association study of Autoimmune and autoinflammatory diseases by integrating multi-modal data and hierarchical ontologies.Frontiers in immunology · 2025Article
- Population and Co-Occurrence Characteristics of Diagnoses and Comorbidities in Coronary Artery Disease Patients: A Case Study from a Hospital in Guangxi, China.Bioengineering (Basel, Switzerland) · 2024Article
- A graph theoretical approach to experimental prioritization in genome-scale investigations.Mammalian genome : official journal of the International Mammalian Genome Society · 2024Article
- Lung Tissue Multilayer Network Analysis Uncovers the Molecular Heterogeneity of Chronic Obstructive Pulmonary Disease.American journal of respiratory and critical care medicine · 2024Article
- Combining Data-Driven and Structure-Based Approaches in Designing Dual PARP1-BRD4 Inhibitors for Breast Cancer Treatment.Journal of chemical information and modeling · 2024Article
- PyMulSim: a method for computing node similarities between multilayer networks via graph isomorphism networks.BMC bioinformatics · 2024Article
- Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes.Nature communications · 2024Article
- DbKB a knowledge graph dataset for diabetes: A system biology approach.Data in brief · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Untangling the complex interplay between phenotype and genotype is crucial to the effective characterization and subtyping of diseases. Here we build and analyze the multiplex network of 779 human diseases, which consists of a genotype-based layer and a phenotype-based layer. We show that diseases with common genetic constituents tend to share symptoms, and uncover how phenotype information helps boost genotype information. Moreover, we offer a flexible classification of diseases that considers their molecular underpinnings alongside their clinical manifestations. We detect cohesive groups of diseases that have high intra-group similarity at both the molecular and the phenotypic level. Inspecting these disease communities, we demonstrate the underlying pathways that connect diseases mechanistically. We observe monogenic disorders grouped together with complex diseases for which they increase the risk factor. We propose potentially new disease associations that arise as a unique feature of the information flow within and across the two layers.
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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.