Bioinformatic analysis using complex networks and clustering proteins involved with Alzheimer's disease.

Rujirapapipat, Suthinan, McGarry, Kenneth and Nelson, David (2016) Bioinformatic analysis using complex networks and clustering proteins involved with Alzheimer's disease. In: 16th UK Workshop on Computational Intelligence, UKCI-2016, 7-9 Sep 2016, Lancaster University.

[img]
Preview
PDF
UKCK2016B.pdf - Published Version

Download (986kB) | Preview

Abstract

The detection of protein complexes is an important research problem in bioinformatics, which may help increase our understanding of the biological functions of proteins inside our body. Moreover, new discoveries obtained from identification of protein complexes may be considered important for therapeutic purposes. Several proteins linked with Alzheimer’s disease were investigated. By observing the connectivity between proteins using computational methods such as graph theory and clustering, we can uncover previously unknown relationships that are useful for potential knowledge discovery. Furthermore, we demonstrate how Markov Clustering (MCL) and the Molecular Complex Detection (MCODE) algorithm identify interesting patterns from the protein-protein interaction data related to Alzheimer’s disease.

Item Type: Conference or Workshop Item (Paper)
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46562-3
Subjects: Computing > Artificial Intelligence
Sciences > Health Sciences
Divisions: Faculty of Applied Sciences > Department of Pharmacy Health and Wellbeing
Health Sciences and Wellbeing Beacon
Related URLs:
Depositing User: Kenneth McGarry
Date Deposited: 10 Aug 2016 13:33
Last Modified: 07 Sep 2017 02:38
URI: http://sure.sunderland.ac.uk/id/eprint/6502

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year