Exploring Amyotrophic Lateral Sclerosis (ALS) with PercayAI’s AI Tools
Welcome to our newest blog series where we investigate Amyotrophic Lateral Sclerosis (ALS) using our AI knowledge mapping tools. Check back for our next installment, in which we analyze transcriptomics from spinal cord samples collected from patients as well as a mouse model.
In this post, we will continue to explore publicly available datasets surrounding Amyotrophic Lateral Sclerosis (ALS), a devastating neuromuscular degenerative disease for which there is no cure. If you’re not a neuroscientist and want to quickly get up to speed on the important biological themes in ALS, you may find the knowledge map in our first post helpful. Our second post discussed familial versus sporadic ALS, and used PercayAI’s concept-level comparison tool to identify biological processes and pathways that are similar between these two subsets of the disease.
In our third post of the series, we will analyze a mouse model of ALS. As any preclinical researcher is well aware, mouse models provide powerful and rapid insights into human disease, but can often lead scientists astray if a result does not translate to humans. We’ll use our concept-level comparison tool to identify aspects of the mouse ALS model that are conserved in human familial ALS. This workflow can be used for any area of translational research.