ArticlePLoS computational biology2010
Network-based elucidation of human disease similarities reveals common functional modules enriched for pluripotent drug targets.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 155 papers, 1 of them a synthesis that pooled it.
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Who cites it
155 citing papers in PubMed, 1 synthesis or guideline pooled it, 338 citations in OpenAlex.
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- Identifying Qingkailing ingredients-dependent mesenchymal-epithelial transition factor-axiation "π" structuring module with angiogenesis and neurogenesis effects.Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan · 2024Article
- Altered expression of the L-arginine/nitric oxide pathway in ovarian cancer: metabolic biomarkers and biological implications.BMC cancer · 2023Article
- DapBCH: a disease association prediction model Based on Cross-species and Heterogeneous graph embedding.Frontiers in genetics · 2023Article
- Exploring novel disease-disease associations based on multi-view fusion network.Computational and structural biotechnology journal · 2023Article
- Computational systems biology in disease modeling and control, review and perspectives.NPJ systems biology and applications · 2022Review
- Clinical diagnosis of metabolic disorders using untargeted metabolomic profiling and disease-specific networks learned from profiling data.Scientific reports · 2022Article
- A multi-network integration approach for measuring disease similarity based on ncRNA regulation and heterogeneous information.BMC bioinformatics · 2022Article
- Development and validation of a prognostic and predictive 32-gene signature for gastric cancer.Nature communications · 2022Article
- BrainBase: a curated knowledgebase for brain diseases.Nucleic acids research · 2022Article
- GPCRs Are Optimal Regulators of Complex Biological Systems and Orchestrate the Interface between Health and Disease.International journal of molecular sciences · 2021Review
- Identifying Novel Drug Targets by iDTPnd: A Case Study of Kinase Inhibitors.Genomics, proteomics & bioinformatics · 2021Article
- Identifying diseases that cause psychological trauma and social avoidance by GCN-Xgboost.BMC bioinformatics · 2020Article
- Article
- Network analysis of autistic disease comorbidities in Chinese children based on ICD-10 codes.BMC medical informatics and decision making · 2020Article
- PS4DR: a multimodal workflow for identification and prioritization of drugs based on pathway signatures.BMC bioinformatics · 2020Article
- Interpreting molecular similarity between patients as a determinant of disease comorbidity relationships.Nature communications · 2020Article
95 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional modules in the human protein network and provided a quantitative metric to record their responses in 54 diseases leading to 138 significant similarities between diseases. Fourteen of the significant disease correlations also shared common drugs, supporting the hypothesis that similar diseases can be treated by the same drugs, allowing us to make predictions for new uses of existing drugs. Finally, we also identified 59 modules that were dysregulated in at least half of the diseases, representing a common disease-state "signature". These modules were significantly enriched for genes that are known to be drug targets. Interestingly, drugs known to target these genes/proteins are already known to treat significantly more diseases than drugs targeting other genes/proteins, highlighting the importance of these core modules as prime therapeutic opportunities.
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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.