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The current text makes us informative about clustering methods used to generate phylogenetic trees by both distance- and character-based analyses.
Our analysis indicates that characters from both base-pairing regions (stems) and non-base-pairing regions (loops) contain phylogenetic information, as judged by the level of support of the phylogenetic results compared with a well-established tree based on both morphological and molecular data.
As with any partitioning of data, character exclusion may lead to weaker phylogenetic hypotheses, and the practice of mapping characters onto a tree, rather than including them in the analysis, should be avoided.
We suggest using k-mer distance for fast, approximate phylogenetic tree construction, and show that a speed improvement of more than three orders of magnitude can be achieved relative to standard distance methods, which require alignments.
We propose a new format for storing phylogenetic trees that significantly reduces storage requirements while continuing to allow the trees to be used as input to post-tree analysis.
Character statements with a wide scope are desirable because they refer to characters with the potential to resolve deep nodes in phylogenetic analyses.
This technique can be used in conjunction with any method of phylogenetic character analysis to construct a tree, showing in summary form more of the information in the data matrix.
Open accessJournal ArticleDOI
59 Citations
The results show that we can build a phylogenetic tree based on the information collected.
This algorithm can be used to construct phylogenetic trees from DNA sequences.
The distance matrix output of DNAWD is shown to provide a good estimate of the associated phylogenetic tree.
The implementation of secondary structure information into character-based phylogenetic methods is suggested to further improve the versatility of this marker in phylogenetic studies.
Therefore, we recommend that morphological systematists routinely implement a range of character transformation models to assess the sensitivity of their phylogenetic reconstructions.

Related Questions

What is basic concepts for phylogenetic tree construction?5 answersPhylogenetic tree construction involves several basic concepts. First, a phylogenetic tree describes the ancestor-descendant relationships of a set of entities, such as species or genes. The leaves of the tree represent present-day entities, while the internal nodes represent common ancestors from the past. The construction of a phylogenetic tree is based on the genetic distance between species, which can be calculated using alignment-based sequencing or alignment-free sequencing methods. Once the genetic distances are calculated, a machine learning-based algorithm can be used to construct the phylogenetic tree. There are also different approaches for phylogenetic reconstruction, including distance-based phylogenetic reconstruction, maximum parsimony, and maximum likelihood. Finally, consensus methods and bootstrapping can be used to compare multiple phylogenies and assess confidence in the tree construction.
Compared with ML method, is NJ method more suitable for SNP information to construct phylogenetic trees?5 answersThe neighbor joining (NJ) method is generally more suitable than the maximum likelihood (ML) method for constructing phylogenetic trees based on SNP information. Computer simulations have shown that the NJ method with p distance (NJp method) gives better performance than other methods, regardless of whether the gene is compositional or contains mosaic DNA regions. NJp method generally gives a high value of the combined quantity (c), which indicates a good data-fit model. Additionally, the SNPhylo pipeline, which uses a maximum likelihood method, is specifically designed to construct phylogenetic trees based on large SNP datasets. Therefore, the NJ method is more accurate and suitable for constructing phylogenetic trees using SNP information compared to the ML method.
What are phylogenetic trees useful for?3 answersPhylogenetic trees are useful for studying evolutionary relationships, ecological patterns, and epidemiological phenomena. They provide a way to model hierarchical data and encode information about species, genes, and patterns of ancestry. Phylogenetic trees can be used to analyze and compare tree distributions, summarize samples of trees, and assess the stability and generalizability of these summaries. They also serve as a method for monitoring changes and detecting viral variants, particularly in the context of biomedicine and studying SARS-CoV-2. Additionally, phylogenetic trees can be used for parameter estimation, model selection, and tree clustering, providing distance-based likelihood-free methods. Overall, phylogenetic trees are a powerful tool for understanding evolutionary processes and analyzing complex biological data.
What software is used for phylogenetic tree?6 answers
Which software is used for phylogenetic tree?16 answers
Who invented phylogenetic tree?5 answers

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