CLAST
Clustering Biological Sequences
Vicente Molieri; Lina J. Karam; Zoé Lacroix School of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ, USA
Abstract
Clustering sequences is important in a variety of applications, including development of nonredundant databases, function prediction, and identifying patterns of gene expression. Currently, clustering methods rely on a prealignment as supplementary information to guide the construction of clusters. This chapter introduces a novel algorithm to cluster nucleotide and peptide sequences. The algorithm is a no-reference approach that utilizes only the sequences as input. We also introduce a novel metric that is used to describe the relationship ...
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