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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Rujirapipat, S., McGarry, K., Nelson, D. (2017). Bioinformatic Analysis Using Complex Networks and Clustering Proteins Linked with Alzheimer’s Disease. In: Angelov, P., Gegov, A., Jayne, C., Shen, Q. (eds) Advances in Computational Intelligence Systems. Advances in Intelligent Systems and Computing, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-319-46562-3_14
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DOI: https://doi.org/10.1007/978-3-319-46562-3_14
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