A few logs suffice to build (almost) all trees. II

From MaRDI portal
Publication:1960520

DOI10.1016/S0304-3975(99)00028-6zbMath0933.68100OpenAlexW2066327035MaRDI QIDQ1960520

Péter L. Erdős, László A. Székely, Tandy J. Warnow, Mike A. Steel

Publication date: 12 January 2000

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-3975(99)00028-6




Related Items

Circular Networks from Distorted MetricsFast and reliable reconstruction of phylogenetic trees with indistinguishable edgesCyclic permutations and evolutionary treesAverage case analysis for tree labelling schemesComparing evolutionary distances via adaptive distance functionsOn the variational distance of two treesFast and accurate branch support calculation for distance-based phylogenetic placementsFast error-tolerant quartet phylogeny algorithmsCombinatorial statistics and the sciencesUnnamed ItemLearning a tree-structured Ising model in order to make predictionsAlignment-free phylogenetic reconstruction: Sample complexity via a branching process analysisFast phylogeny reconstruction through learning of ancestral sequencesLearning Minimal Latent Directed Information PolytreesOn the hardness of inferring phylogenies from triplet-dissimilaritiesFast Error-Tolerant Quartet Phylogeny AlgorithmsThe matroid structure of representative triple sets and triple-closure computationPhase transition in the sample complexity of likelihood-based phylogeny inferenceLearning nonsingular phylogenies and hidden Markov modelsUnnamed ItemNetwork delay inference from additive metricsThe impact and interplay of long and short branches on phylogenetic information contentPhase transitions in phylogenyRapidly computing the phylogenetic transfer indexLarge-Scale Multiple Sequence Alignment and Phylogeny EstimationTopology discovery of sparse random graphs with few participantsInverting random functionsAncestral state reconstruction with large numbers of sequences and edge-length estimation



Cites Work