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Information 2015, 6(4), 811-832; doi:10.3390/info6040811

Information and Phylogenetic Systematic Analysis

1,2,3
and
3,4,5,*
1
Department of Mathematics and Statistics, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada
2
Fields Institute for Research in Mathematical Sciences, 222 College Street, Toronto, ON M5T 3J1, Canada
3
Origins Institute, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4M1, Canada
4
Department of Biology, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada
5
Shared Hierarchical Academic Research Computing Network, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4L8, Canada
*
Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 3 September 2015 / Revised: 28 November 2015 / Accepted: 30 November 2015 / Published: 8 December 2015
(This article belongs to the Section Information Theory and Methodology)
View Full-Text   |   Download PDF [798 KB, uploaded 9 December 2015]   |  

Abstract

Information in phylogenetic systematic analysis has been conceptualized, defined, quantified, and used differently by different authors. In this paper, we start with the Shannon Uncertainty Measure information measure I, applying it to cladograms containing only consistent character states. We formulate a general expression for I, utilizing a standard format for taxon-character matrices, and investigate the effect that adding data to an existing taxon-character matrix has on I. We show that I may increase when character vectors that encode autapomorphic or synapomorphic character states are added. However, as added character vectors accumulate, I tends to a limit, which generally is less than the maximum I. We show computationally and analytically that limc→∞ I = log2 t, in which t enumerates taxa and c enumerates characters. For any particular t, upper and lower bounds in I exist. We use our observations to suggest several interpretations about the relationship between information and phylogenetic systematic analysis that have eluded previous, precise recognition. View Full-Text
Keywords: cladistic analysis; cladogram; Shannon uncertainty measure; surprisal analysis; systematic classification; taxonomy cladistic analysis; cladogram; Shannon uncertainty measure; surprisal analysis; systematic classification; taxonomy
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Craig, W.; Stone, J. Information and Phylogenetic Systematic Analysis. Information 2015, 6, 811-832.

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