• Corpus ID: 53372069

Introduction to Computational Phylogenetics

  title={Introduction to Computational Phylogenetics},
  author={Tandy J. Warnow},
This manuscript is a draft, and should not be distributed. Some of the material in this text appeared verbatim in unpublished notes for the course " Computational methods in linguistic reconstruction " taught for the LSA Institute in 2009 at the 
Using Quartets to Compare the NCD and MCMC Methods for Constructing Phylogenetic Trees
  • J. Rogers
  • Computer Science
    2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  • 2018
Results are looked at at results comparing the Normalized Compression Distance and Markov Chain Monte Carlo methods with respect to unrooted quartet trees, which can serve as building blocks for deriving trees on larger sets of sequences.
The Bhargava greedoid
The greedoids (as defined in 1981 by Korte and Lóvász) are a class of set systems similar to the matroids (but more permissive). Inspired by Bhargava’s generalized factorials, we introduce a greedoid


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On the optimization principle in phylogenetic analysis and the minimum-evolution criterion.
  • O. Gascuel
  • Computer Science
    Molecular biology and evolution
  • 2000
It is shown that the minimum-evolution criterion is not perfectly suited for distance data estimated from sequences, and another approach is presented, implemented in the BIONJ algorithm, which allows the data features to be taken into account, while being less demanding in computing time.
A short proof that phylogenetic tree reconstruction by maximum likelihood is hard
  • S. Roch
  • Biology
    IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • 2006
A short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.
A classification of consensus methods for phylogenetics
This paper surveys the main consensus tree methods used in phylogenetics, and explores the links between the different methods, producing a classification of consensus Tree methods.
Faster reliable phylogenetic analysis
Fast new algorithms for phylogenetic reconstruction from distance data or weighted quartets are presented, and an attractive duality between unrooted trees, splits, and dissimilarities on one hand, and rooted trees, clusters, and similarity measures on the other is introduced.
The Performance of Neighbor-Joining Methods of Phylogenetic Reconstruction
An upper bound on the amount of data necessary to reconstruct the topology with high confidence is demonstrated by finding conditions under which these methods will determine the correct tree topology and showing that these perform as well as possible in a certain sense.
ProtTest: selection of best-fit models of protein evolution
This work has built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment in order to study protein evolution and phylogenetic inference.
Inferring a Tree from Lowest Common Ancestors with an Application to the Optimization of Relational Expressions
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WO is faster and offers better theoretical guarantees than QP, a new algorithm which is also based on weighted 4-trees, and computer simulations indicate that the topological accuracy of WO is less dependent on the shape of the correct tree.
Phylogenetic analysis: concepts and methods.
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