Related Experiment Video
Updated: May 20, 2026

A Quick Phenotypic Neurological Scoring System for Evaluating Disease Progression in the SOD1-G93A Mouse Model of ALS
Published on: October 6, 2015
ALSoD: A user-friendly online bioinformatics tool for amyotrophic lateral sclerosis genetics
Olubunmi Abel1, John F Powell, Peter M Andersen
1Department of Clinical Neuroscience, King's College London, Institute of Psychiatry, London, UK.
Abstract:
Amyotrophic lateral sclerosis (ALS) is the commonest adult onset motor neuron disease, with a peak age of onset in the seventh decade. With advances in genetic technology, there is an enormous increase in the volume of genetic data produced, and a corresponding need for storage, analysis, and interpretation, particularly as our understanding of the relationships between genotype and phenotype mature. Here, we present a system to enable this in the form of the ALS Online Database (ALSoD at http://alsod.iop.kcl.ac.uk), a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.
