Paper Info
Title
Reasoning over genetic variance information in cause-and-effect models of neurodegenerative diseases.
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.
Year
DOI
Venue
2016
10.1093/bib/bbv063
BRIEFINGS IN BIOINFORMATICS
Keywords
Field
DocType
BEL model,Alzheimer's disease,genetic variants,GWAS,causal reasoning,cause-and-effect
Disease,Systems biomedicine,Biology,microRNA,Genetic variation,Single-nucleotide polymorphism,Bioinformatics
Journal
Volume
Issue
ISSN
17
SP3
1467-5463
Citations 
PageRank 
References 
3
0.62
15
Authors
3
Name
Order
Citations
PageRank
mufassra naz171.22
alpha tom kodamullil2153.08
Martin Hofmann-Apitius337230.08