Selected article for: "computational cost and likelihood estimation"
Author: Gardner, Paul P.; Daub, Jennifer; Tate, John G.; Nawrocki, Eric P.; Kolbe, Diana L.; Lindgreen, Stinus; Wilkinson, Adam C.; Finn, Robert D.; Griffiths-Jones, Sam; Eddy, Sean R.; Bateman, Alex
Title: Rfam: updates to the RNA families database
  • Document date: 2008_10_25
    • ID: wj7yonjw_8
    Snippet: Phylogenetic trees have been estimated for both the SEED and FULL alignments. For the majority of the alignments we produced the trees using an accurate maximum-likelihood approach, which included models of indels (6) . However, the computational complexity of tree estimation meant that maximum-likelihood was not always possible and hence, where the number of sequences in the alignment was greater than 64, a neighbour-joining method was used inst.....
    Document: Phylogenetic trees have been estimated for both the SEED and FULL alignments. For the majority of the alignments we produced the trees using an accurate maximum-likelihood approach, which included models of indels (6) . However, the computational complexity of tree estimation meant that maximum-likelihood was not always possible and hence, where the number of sequences in the alignment was greater than 64, a neighbour-joining method was used instead (7). Large alignments and trees are problematic, both in terms of the computational cost of generation and the challenges of displaying them. Therefore, where the number of sequences in the alignment was greater than 1024, the highly similar sequences were filtered by sequence similarity, resulting in relatively sparse and easily presented trees that required comparatively little computing power to generate.

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