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        <identifier>oai:drops-oai.dagstuhl.de:9067</identifier>
        <datestamp>2024-03-06T10:43:17Z</datestamp>
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          <dc:title>A Faster Construction of Greedy Consensus Trees</dc:title>
          <dc:creator>Gawrychowski, Pawel</dc:creator>
          <dc:creator>Landau, Gad M.</dc:creator>
          <dc:creator>Sung, Wing-Kin</dc:creator>
          <dc:creator>Weimann, Oren</dc:creator>
          <dc:subject>phylogenetic trees</dc:subject>
          <dc:subject>greedy consensus trees</dc:subject>
          <dc:subject>dynamic trees</dc:subject>
          <dc:description>A consensus tree is a phylogenetic tree that captures the similarity between a set of conflicting phylogenetic trees. The problem of computing a consensus tree is a major step in phylogenetic tree reconstruction. It is also central for predicting a species tree from a set of gene trees, as indicated recently in [Nature 2013].
This paper focuses on two of the most well-known and widely used consensus tree methods: the greedy consensus tree and the frequency difference consensus tree. Given k conflicting trees each with n leaves, the previous fastest algorithms for these problems were O(k n^2) for the greedy consensus tree [J. ACM 2016] and O~(min{k n^2, k^2n}) for the frequency difference consensus tree [ACM TCBB 2016]. We improve these running times to O~(k n^{1.5}) and O~(k n) respectively.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Pawel Gawrychowski and Gad M. Landau and Wing-Kin Sung and Oren Weimann</dc:contributor>
          <dc:date>2018</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 107, 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.ICALP.2018.63</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-90676</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2018.63</dc:identifier>
          <dc:language>eng</dc:language>
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