ArticleScience (New York, N.Y.)2015
Disease networks. Uncovering disease-disease relationships through the incomplete interactome.
Article in Science (New York, N.Y.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 785 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
785 citing papers in PubMed, 3 syntheses or guidelines pooled it, 1,570 citations in OpenAlex.
- Pooled it
- Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry.Nature communications · 2023Pooled it
- Drug repurposing on Alzheimer's disease through modulation of NRF2 neighborhood.Redox biology · 2023Pooled it
- Synergistic Network Pharmacology: Preclinical Validation and Clinical Safety in Acute Ischemic Stroke.Journal of the American Heart Association · 2025Trial
- Ontological deskilling: clinical expertise and the changing disease object in precision medicine.Medicine, health care, and philosophy · 2026Article
- Artificial intelligence models Traditional Chinese Medicine principles to integrate with biomedicine.iMeta · 2026Article
- Review
- Network Pharmacology-Guided Phytochemical Polypharmacology: Integrating Molecular Mechanisms, Experimental Validation and Clinical Translation.International journal of molecular sciences · 2026Review
- A Drug-Referenced Machine-Learning Framework for Prioritizing Korean Herbal Formulations in Hypertension Using Linear SVM and Graph Convolutional Networks.International journal of molecular sciences · 2026Article
- Functional Annotation of Alzheimer's Disease-Associated SNPs Based on Three-Dimensional Chromatin Structure.International journal of molecular sciences · 2026Article
- Beyond Structural Representations: A Semantic-Relational Graph Neural Network for Polypharmacy Side Effect Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- In-silico personalized protein-protein interaction networks prioritize candidate compounds for glioblastoma.PLoS computational biology · 2026Article
- CAREPath: semantic context-aware reasoning paths with mechanism-augmented embeddings for drug repurposing.Briefings in bioinformatics · 2026Article
- Revisiting retinal and macular degeneration in the genomics era.Nature reviews. Genetics · 2026Review
- MKLNID: Identifying Melanoma-related Pathogenic Genes Through Multiple Kernel Learning and Network Impulsive Dynamics.Interdisciplinary sciences, computational life sciences · 2026Article
- Peroxisomal interactome mapping enables network-based modelling of function and disease.Life science alliance · 2026Article
- TargetPrior: a miRNA-signature embedded evolutionary learning framework for prioritizing drug targets in acute myeloid leukemia.Bioinformatics (Oxford, England) · 2026Article
- Target-biology and interactome-derived signatures predict target-level associations with safety-related drug attrition.Scientific reports · 2026Article
- Nuclear RSK1 mediates interferon-γ-induced proinflammatory activation in human primary macrophages and humanized mice.Science advances · 2026Article
- Article
725 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 4 institutions in 1 country.
Funding
Abstract
According to the disease module hypothesis, the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data have sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant coexpression patterns, symptom similarity, and comorbidity, whereas diseases residing in separated network neighborhoods are phenotypically distinct. These tools represent an interactome-based platform to predict molecular commonalities between phenotypically related diseases, even if they do not share primary disease genes.
Indexed as
Identifiers
What OpenQuestion holds
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.