On parsimony and clustering
This work is motivated by applications of parsimonious cladograms for the purpose of analyzing non-biological data. Parsimonious cladograms were introduced as a means to help understanding the tree of life, and are now used in fields related to biological sciences at large, e.g., to analyze viruses...
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sg-ntu-dr.10356-1692922023-07-14T15:35:54Z On parsimony and clustering Oggier, Frederique Datta, Anwitaman School of Computer Science and Engineering School of Physical and Mathematical Sciences Engineering::Computer science and engineering Parsimony Clustering This work is motivated by applications of parsimonious cladograms for the purpose of analyzing non-biological data. Parsimonious cladograms were introduced as a means to help understanding the tree of life, and are now used in fields related to biological sciences at large, e.g., to analyze viruses or to predict the structure of proteins. We revisit parsimonious cladograms through the lens of clustering and compare cladograms optimized for parsimony with dendograms obtained from single linkage hierarchical clustering. We show that despite similarities in both approaches, there exist datasets whose clustering dendogram is incompatible with parsimony optimization. Furthermore, we provide numerical examples to compare via F-scores the clustering obtained through both parsimonious cladograms and single linkage hierarchical dendograms. Published version 2023-07-11T06:16:50Z 2023-07-11T06:16:50Z 2023 Journal Article Oggier, F. & Datta, A. (2023). On parsimony and clustering. PeerJ Computer Science, 9, e1339-. https://dx.doi.org/10.7717/peerj-cs.1339 2376-5992 https://hdl.handle.net/10356/169292 10.7717/peerj-cs.1339 37346541 9 e1339 en PeerJ Computer science © 2023 Oggier and Datta. Distributed under Creative Commons CC-BY 4.0. application/pdf |
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Engineering::Computer science and engineering Parsimony Clustering Oggier, Frederique Datta, Anwitaman On parsimony and clustering |
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This work is motivated by applications of parsimonious cladograms for the purpose of analyzing non-biological data. Parsimonious cladograms were introduced as a means to help understanding the tree of life, and are now used in fields related to biological sciences at large, e.g., to analyze viruses or to predict the structure of proteins. We revisit parsimonious cladograms through the lens of clustering and compare cladograms optimized for parsimony with dendograms obtained from single linkage hierarchical clustering. We show that despite similarities in both approaches, there exist datasets whose clustering dendogram is incompatible with parsimony optimization. Furthermore, we provide numerical examples to compare via F-scores the clustering obtained through both parsimonious cladograms and single linkage hierarchical dendograms. |
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School of Computer Science and Engineering |
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School of Computer Science and Engineering Oggier, Frederique Datta, Anwitaman |
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Article |
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Oggier, Frederique Datta, Anwitaman |
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Oggier, Frederique |
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On parsimony and clustering |
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On parsimony and clustering |
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On parsimony and clustering |
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On parsimony and clustering |
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On parsimony and clustering |
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on parsimony and clustering |
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2023 |
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https://hdl.handle.net/10356/169292 |
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