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.
Item Type: | Conference or Workshop Item (Paper) |
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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.
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Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-46562-3 |
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Depositing User: Kenneth McGarry |
Identifiers
Item ID: 6502 |
URI: http://sure.sunderland.ac.uk/id/eprint/6502 | Official URL: http://wp.lancs.ac.uk/ukci2016/ |
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Catalogue record
Date Deposited: 10 Aug 2016 13:33 |
Last Modified: 18 Dec 2019 15:39 |
Author: | Kenneth McGarry |
Author: | Suthinan Rujirapapipat |
Author: | David Nelson |
University Divisions
Faculty of TechnologyFaculty of Technology > School of Computer Science
Subjects
Computing > Artificial IntelligenceSciences > Health Sciences
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