2018
DOI: 10.1007/978-3-319-92016-0_18
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A Multi-metric Algorithm for Hierarchical Clustering of Same-Length Protein Sequences

Abstract: The identification of meaningful groups of proteins has always been a major area of interest for structural and functional genomics. Successful protein clustering can lead to significant insight, assisting in both tracing the evolutionary history of the respective molecules as well as in identifying potential functions and interactions of novel sequences. Here we propose a clustering algorithm for same-length sequences, which allows the construction of subset hierarchy and facilitates the identification of the… Show more

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Cited by 2 publications
(1 citation statement)
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“…Since the main algorithm makes use of the frequency of occurrence of the main terms in the documents, we call it Frequencybased Hierarchical Clustering (FBHC). A relevant clustering method that we presented in one of our previous works [36] makes use of frequency matrices to construct an hierarchy of biological sequences.…”
Section: Document Clusteringmentioning
confidence: 99%
“…Since the main algorithm makes use of the frequency of occurrence of the main terms in the documents, we call it Frequencybased Hierarchical Clustering (FBHC). A relevant clustering method that we presented in one of our previous works [36] makes use of frequency matrices to construct an hierarchy of biological sequences.…”
Section: Document Clusteringmentioning
confidence: 99%