ArticleBMC medical genomics2017
A disease similarity matrix based on the uniqueness of shared genes.
Article in BMC medical genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- CaSSiDI: novel single-cell "Cluster Similarity Scoring and Distinction Index" reveals critical functions for PirB and context-dependent Cebpb repression.Cell death and differentiation · 2024Article
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- Classifying diseases by using biological features to identify potential nosological models.Scientific reports · 2021Article
- PCOSKBScientific reports · 2020Article
- Construction of Disease Similarity Networks Using Concept Embedding and Ontology.Studies in health technology and informatics · 2019Article
- VCF-Server: A web-based visualization tool for high-throughput variant data mining and management.Molecular genetics & genomic medicine · 2019Article
- Functional Site Discovery From Incomplete Training Data: A Case Study With Nucleic Acid-Binding Proteins.Frontiers in genetics · 2019Article
- A Novel Joint Gene Set Analysis Framework Improves Identification of Enriched Pathways in Cross Disease Transcriptomic Analysis.Frontiers in genetics · 2019Article
- Maternal Cognitive Impairment Associated with Gestational Diabetes Mellitus-A Review of Potential Contributing Mechanisms.International journal of molecular sciences · 2018Review
- PedAM: a database for Pediatric Disease Annotation and Medicine.Nucleic acids research · 2018Article
- eRAM: encyclopedia of rare disease annotations for precision medicine.Nucleic acids research · 2018Article
- Evolution of Translational Bioinformatics: lessons learned from TBC 2016.BMC medical genomics · 2017Article
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Authors and funding
5 authors.
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Abstract
backgroundComplex diseases involve many genes, and these genes are often associated with several different illnesses. Disease similarity measurement can be based on shared genotype or phenotype. Quantifying relationships between genes can reveal previously unknown connections and form a reference base for therapy development and drug repurposing.
methodsHere we introduce a method to measure disease similarity that incorporates the uniqueness of shared genes. For each disease pair, we calculated the uniqueness score and constructed disease similarity matrices using OMIM and Disease Ontology annotation.
resultsUsing the Disease Ontology-based matrix, we identified several interesting connections between cancer and other disease and conditions such as malaria, along with studies to support our findings. We also found several high scoring pairwise relationships for which there was little or no literature support, highlighting potentially interesting connections warranting additional study.
conclusionsWe developed a co-occurrence matrix based on gene uniqueness to examine the relationships between diseases from OMIM and DORIF data. Our similarity matrix can be used to identify potential disease relationships and to motivate further studies investigating the causal mechanisms in diseases.
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