Reproduce maxcrees/tbl.typ #11

references.bib

@article{hein1996,
  title = {On the Complexity of Comparing Evolutionary Trees},
  author = {Hein, Jotun and Jiang, Tao and Wang, Lusheng and Zhang, Kaizhong},
  date = {1996-12-05},
  journaltitle = {Discrete Applied Mathematics},
  shortjournal = {Discrete Applied Mathematics},
  volume = {71},
  number = {1},
  pages = {153--169},
  issn = {0166-218X},
  doi = {10.1016/S0166-218X(96)00062-5},
  urldate = {2023-08-24},
  abstract = {We study the computational complexity and approximation of several problems arising in the comparison of evolutionary trees. It is shown that the maximum agreement subtree (MAST) problem for three trees with unbounded degree cannot be approximated within ratio 2logδ n in polynomial time for any δ {$<$} 1, unless NP ⊆ DTIME[2polylog n], and MAST with edge contractions for two binary trees is NP-hard. This answers two open questions posed in [1]. For the maximum refinement subtree (MRST) problem involving two trees, we show that it is polynomial-time solvable when both trees have bounded degree and is NP-hard when one of the trees can have an arbitrary degree. Finally, we consider the problem of optimally transforming a tree into another by transferring subtrees around. It is shown that computing the subtree-transfer distance is NP-hard and an approximation algorithm with performance ratio 3 is given.},
  keywords = {Approximation algorithm,Compatibility,Computational complexity,Evolutionary tree,Phylogeny,Recombination},
  file = {/Users/tcztzy/Library/CloudStorage/OneDrive-个人/Literatures/Journal Article/Discrete Applied Mathematics/1996/Hein et al_1996_On the complexity of comparing evolutionary trees.pdf;/Users/tcztzy/Zotero/storage/KWMLP5U3/S0166218X96000625.html}
}

@article{kuhner1994,
  title = {A Simulation Comparison of Phylogeny Algorithms under Equal and Unequal Evolutionary Rates},
  author = {Kuhner, M. K. and Felsenstein, J.},
  date = {1994-05},
  journaltitle = {Molecular Biology and Evolution},
  shortjournal = {Mol Biol Evol},
  volume = {11},
  number = {3},
  eprint = {8015439},
  eprinttype = {pmid},
  pages = {459--468},
  issn = {0737-4038},
  doi = {10.1093/oxfordjournals.molbev.a040126},
  abstract = {Using simulated data, we compared five methods of phylogenetic tree estimation: parsimony, compatibility, maximum likelihood, Fitch-Margoliash, and neighbor joining. For each combination of substitution rates and sequence length, 100 data sets were generated for each of 50 trees, for a total of 5,000 replications per condition. Accuracy was measured by two measures of the distance between the true tree and the estimate of the tree, one measure sensitive to accuracy of branch lengths and the other not. The distance-matrix methods (Fitch-Margoliash and neighbor joining) performed best when they were constrained from estimating negative branch lengths; all comparisons with other methods used this constraint. Parsimony and compatibility had similar results, with compatibility generally inferior; Fitch-Margoliash and neighbor joining had similar results, with neighbor joining generally slightly inferior. Maximum likelihood was the most successful method overall, although for short sequences Fitch-Margoliash and neighbor joining were sometimes better. Bias of the estimates was inferred by measuring whether the independent estimates of a tree for different data sets were closer to the true tree than to each other. Parsimony and compatibility had particular difficulty with inaccuracy and bias when substitution rates varied among different branches. When rates of evolution varied among different sites, all methods showed signs of inaccuracy and bias.},
  langid = {english},
  keywords = {Algorithms,Biological Evolution,Computer Simulation,Phylogeny},
  file = {/Users/tcztzy/Library/CloudStorage/OneDrive-个人/Literatures/Journal Article/Molecular Biology and Evolution/1994/Kuhner_Felsenstein_1994_A simulation comparison of phylogeny algorithms under equal and unequal.pdf}
}

@article{priel2022,
  title = {A Vectorial Tree Distance Measure},
  author = {Priel, Avner and Tamir, Boaz},
  date = {2022-03-28},
  journaltitle = {Scientific Reports},
  shortjournal = {Sci Rep},
  volume = {12},
  number = {1},
  pages = {5256},
  publisher = {{Nature Publishing Group}},
  issn = {2045-2322},
  doi = {10.1038/s41598-022-08360-4},
  urldate = {2023-08-24},
  abstract = {A vectorial distance measure for trees is presented. Given two trees, we define a Tree-Alignment (T-Alignment). We T-align the trees from their centers outwards, starting from the root-branches, to make the next level as similar as possible. The algorithm is recursive; condition on the T-alignment of the root-branches we T-align the sub-branches, thereafter each T-alignment is conditioned on the previous one. We define a minimal T-alignment under a lexicographic order which follows the intuition that the differences between the two trees constitutes a vector. Given such a minimal T-alignment, the difference in the number of branches calculated at any level defines the entry of the distance vector at that level. We compare our algorithm to other well-known tree distance measures in the task of clustering sets of phylogenetic trees. We use the TreeSimGM simulator for generating stochastic phylogenetic trees. The vectorial tree distance (VTD)~can successfully separate symmetric from asymmetric trees, and hierarchical from non-hierarchical trees. We also test the algorithm as a classifier of phylogenetic trees extracted from two members of the fungi kingdom, mushrooms and mildews, thus showimg that the algorithm can separate real world phylogenetic trees. The Matlab code can be accessed via: https://gitlab.com/avner.priel/vectorial-tree-distance.},
  issue = {1},
  langid = {english},
  keywords = {Computational biology and bioinformatics,Developmental biology},
  file = {/Users/tcztzy/Library/CloudStorage/OneDrive-个人/Literatures/Journal Article/Scientific Reports/2022/Priel_Tamir_2022_A vectorial tree distance measure.pdf}
}

@article{robinson1981,
  title = {Comparison of Phylogenetic Trees},
  author = {Robinson, D. F. and Foulds, L. R.},
  date = {1981-02-01},
  journaltitle = {Mathematical Biosciences},
  shortjournal = {Mathematical Biosciences},
  volume = {53},
  number = {1},
  pages = {131--147},
  issn = {0025-5564},
  doi = {10.1016/0025-5564(81)90043-2},
  urldate = {2023-08-24},
  abstract = {A metric on general phylogenetic trees is presented. This extends the work of most previous authors, who constructed metrics for binary trees. The metric presented in this paper makes possible the comparison of the many nonbinary phylogenetic trees appearing in the literature. This provides an objective procedure for comparing the different methods for constructing phylogenetic trees. The metric is based on elementary operations which transform one tree into another. Various results obtained in applying these operations are given. They enable the distance between any pair of trees to be calculated efficiently. This generalizes previous work by Bourque to the case where interior vertices can be labeled, and labels may contain more than one element or may be empty.},
  file = {/Users/tcztzy/Zotero/storage/D5Z4H9HV/0025556481900432.html}
}

teat.typ

#import "@preview/tbl:0.0.3"
#show: tbl.template.with(box: true, tab: "|")
#set cite(style: "chicago-author-date")
#figure(
    caption: "Distance between two phylogenetic trees",
    caption-pos: top,
    kind: "table",
    supplement: [Table],
```tbl
C C C C
R N.
Method | Year | Description | Reference
\_     | \_   | \_          | \_
RF     | 1981 | Robinson-Foulds distance | @robinson1981
KF     | 1994 | Kuhner-Felsenstein distance | @kuhner1994
PS     | 1985 | Path similarity |
SPR    | 1996 | Subtree prune and regraft distance | @hein1996
VTD    | 2022 | Vectorial tree distance | @priel2022
```
)
#bibliography("references.bib")