ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2012
Formal concept analysis of disease similarity.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine.Briefings in bioinformatics · 2022Review
- Predicting combinations of drugs by exploiting graph embedding of heterogeneous networks.BMC bioinformatics · 2022Article
- Clustering approaches for visual knowledge exploration in molecular interaction networks.BMC bioinformatics · 2018Article
- Cancer Subtype Discovery Using Prognosis-Enhanced Neural Network Classifier in Multigenomic Data.Technology in cancer research & treatment · 2018Article
- A disease similarity matrix based on the uniqueness of shared genes.BMC medical genomics · 2017Article
- Biobanking across the phenome - at the center of chronic disease research.BMC public health · 2013Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Previous work shows that gene associations and network properties common between pairs of diseases can provide molecular evidence of comorbidity, but relationships among diseases may extend to larger groups. Formal concept analysis allows the study of multiple diseases based on a concept lattice whose structure indicates gene set commonality. We use the concept lattice for gene associations to evaluate the complexity of the relationships among diseases, and to identify concepts whose gene sets are candidates for further functional analysis. For this, we define a heuristic on the lattice structure that allows the identification of concepts whose gene sets indicate strong relationships among the included diseases, which are distinguished from other diseases in the family. Applying this approach to a family of renal diseases we demonstrate that this approach finds gene sets that may be promising for studying common (and differing) mechanism among a family of comorbid or phenotypically related diseases.
Identifiers
22779049PMC3392047What 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.