Disease knowledge assembly models were generated in order to capture the vast knowledge around AD and PD. The language used to build the underlying models is the open source version of the Biological Expression Language (BEL). BEL encodes knowledge-based (mostly literature-derived) “cause and effect” relationships into network models, which can be subjected to causal analysis using quantitative data such as gene expression. The models developed here not only represent a comprehensive view on the core established pathways involved in amyloid processing, but also cover a broad spectrum of events that lead to clinical readouts often seen in AD and PD patients, such as neuro-inflammatory cascades. These models constitute the core of the candidate mechanism graphs that NeuroMMSig, our repository of candidate mechanisms, is based on.
Alzheimer’s Disease Model (generated by Dr. Alpha Tom Kodamullil and curation team):
35.266 citations and 44.437 BEL statements => 9.645 nodes and 10.251 edges.
Reference: Tom-Kodamullil A., Younesi, E., Naz, M., Bagewadi, S., & Hofmann-Apitius, M. (2015). Computable cause-and-effect models of healthy and Alzheimer's disease states and their mechanistic differential analysis. Alzheimer's & Dementia, 11(11), 1329-1339.
Parkinson’s Disease Model (Reagon Karki and curation team): 432 Citations and 2.236 BEL statements => 1424 nodes and 2.690 Edges.