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- W2473308841 abstract "Clustering is the task of grouping objects based on some similarity metric. Objects in a cluster should be closer to each other than the rest of the objects under consideration. Our aim in this chapter is to describe and analyze clustering algorithms for biological sequences. Classical algorithms may be used for this purpose; however, even the polynomial time algorithms may be time-consuming for DNA, and protein sequences which have very large sizes. We start this chapter by outlining validation methods of clustering and the classical clustering schemes which are the hierarchical clustering and partitional clustering methods. We then describe clustering methods that target biological sequences and outline graph-based clustering methods which can be used for this purpose. There are a number of distributed algorithms for sequence clustering as we discuss. Four new algorithms and a general method for graph partitioning are also proposed which can be implemented in a distributed memory system conveniently." @default.
- W2473308841 created "2016-07-22" @default.
- W2473308841 creator A5021868439 @default.
- W2473308841 date "2015-01-01" @default.
- W2473308841 modified "2023-09-27" @default.
- W2473308841 title "Clustering of Biological Sequences" @default.
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- W2473308841 doi "https://doi.org/10.1007/978-3-319-24966-7_7" @default.
- W2473308841 hasPublicationYear "2015" @default.
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