Development of tools for automated collection, integration and analysis of genetic data in ALS

<br/>Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig’s disease, typically leads to death within 3-5 years of symptom onset. Understanding what causes ALS has been a challenge, but more research in this area, enhanced by advanced technology like high-throughput next generation sequencing, is paving the way for better information and direction. The volume of data generated by genetics researchers has dramatically increased, largely because of increased opportunities for collaboration. ALSoD, a widely used online genetics database for collating, analysing and integrating ALS data, has been updated with analytics tools and is able to portray the data graphically to users. Mutations and other gene variants have been mapped to genomic coordinates, and the inclusion of dbSNP ids has been implemented to facilitate the integration of data from <br/>numerous public sources. To increase the usability and functionality of ALSoD, population frequency of each variant found in the 1000 Genome Project and Exome Variation Server (EVS) databases is displayed. To contribute to a better understanding of the pathogenesis of ALS, links to information on animal models are also available. Furthermore, ALSoD can now be viewed on mobile devices and for Android platforms a mobile app is also available.<br/>

Name dc:type.qualificationname

Doctor of Philosophy

Level dc:type.qualificationlevel

Doctoral Thesis

Grantor dc:publisher.institution

King's College London

Year dc:date.issued

2014

Author dc:creator

• Abel, Olubunmi

Advisors dc:contributor.advisor

• Powell, John F
• Al-Chalabi, Ammar

Language dc:language

eng

Identifier

oai:kclpure.kcl.ac.uk:studenttheses/d7183af6-8965-41db-b1b6-8c07a7a304b6

OAI identifier oai:identifier

oai:kclpure.kcl.ac.uk:studenttheses/d7183af6-8965-41db-b1b6-8c07a7a304b6