Pattern identification in biogeography.

IEEE/ACM Trans Comput Biol Bioinform

Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA.

Published: January 2007

AI Article Synopsis

  • Identifying common patterns in area cladograms helps with biogeographical analysis.
  • A formal methodology is established to compare these cladograms and identify patterns.
  • Algorithms for finding the maximum agreement area cladogram (MAAC) are developed, along with a method for checking if two cladograms are identical.

Article Abstract

Identifying common patterns among area cladograms that arise in historical biogeography is an important tool for biogeographical inference. We develop the first rigorous formalization of these pattern-identification problems. We develop metrics to compare area cladograms. We define the maximum agreement area cladogram (MAAC) and we develop efficient algorithms for finding the MAAC of two area cladograms, while showing that it is NP-hard to find the MAAC of several binary area cladograms. We also describe a linear-time algorithm to identify if two area cladograms are identical.

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Source
http://dx.doi.org/10.1109/TCBB.2006.57DOI Listing

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