ArticleBriefings in bioinformatics2016
Reasoning over genetic variance information in cause-and-effect models of neurodegenerative diseases.
Article in Briefings in bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Neuro-psycho MMSig: multimodal mechanism enrichment platform for neuropsychiatric disorders.Frontiers in bioinformatics · 2026Article
- Navigating the disease landscape: knowledge representations for contextualizing molecular signatures.Briefings in bioinformatics · 2019Review
- Re-curation and rational enrichment of knowledge graphs in Biological Expression Language.Database : the journal of biological databases and curation · 2019Article
- Multimodal mechanistic signatures for neurodegenerative diseases (NeuroMMSig): a web server for mechanism enrichment.Bioinformatics (Oxford, England) · 2017Article
- MAP3K1 May be a Promising Susceptibility Gene for Type 2 Diabetes Mellitus in an Iranian Population.International journal of molecular and cellular medicine · 2016Article
- Training and evaluation corpora for the extraction of causal relationships encoded in biological expression language (BEL).Database : the journal of biological databases and curation · 2016Article
- Bioinformatics Mining and Modeling Methods for the Identification of Disease Mechanisms in Neurodegenerative Disorders.International journal of molecular sciences · 2015Review
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Authors and funding
3 authors.
Funding
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Abstract
The work we present here is based on the recent extension of the syntax of the Biological Expression Language (BEL), which now allows for the representation of genetic variation information in cause-and-effect models. In our article, we describe, how genetic variation information can be used to identify candidate disease mechanisms in diseases with complex aetiology such as Alzheimer's disease and Parkinson's disease. In those diseases, we have to assume that many genetic variants contribute moderately to the overall dysregulation that in the case of neurodegenerative diseases has such a long incubation time until the first clinical symptoms are detectable. Owing to the multilevel nature of dysregulation events, systems biomedicine modelling approaches need to combine mechanistic information from various levels, including gene expression, microRNA (miRNA) expression, protein-protein interaction, genetic variation and pathway. OpenBEL, the open source version of BEL, has recently been extended to match this requirement, and we demonstrate in our article, how candidate mechanisms for early dysregulation events in Alzheimer's disease can be identified based on an integrative mining approach that identifies 'chains of causation' that include single nucleotide polymorphism information in BEL models.
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