1. Introduction

- Presented
Kapli, P., Yang, Z., & Telford, M. J. (2020). Phylogenetic tree building in the genomic age. Nature Reviews. Genetics, 21(7), 428–444.
Iantorno, S., Gori, K., Goldman, N., Gil, M., & Dessimoz, C. (2014). Who watches the watchmen? An appraisal of benchmarks for multiple sequence alignment. Methods in Molecular Biology (Clifton, N.J.), 1079, 59–73.

- Introduced tools
[Sequence alignment] Katoh, K., & Standley, D. M. (2013). MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability. Molecular Biology and Evolution, 30(4), 772–780.
[Sequence alignment] Sievers, F., Wilm, A., Dineen, D., Gibson, T. J., Karplus, K., Li, W., Lopez, R., McWilliam, H., Remmert, M., Söding, J., Thompson, J. D., & Higgins, D. G. (2011). Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Molecular Systems Biology, 7(1), 539.
[Sequence alignment] Löytynoja, A. (2014). Phylogeny-aware alignment with PRANK. Methods in Molecular Biology (Clifton, N.J.), 1079, 155–170.
[Tree inference] Minh, B. Q., Schmidt, H. A., Chernomor, O., Schrempf, D., Woodhams, M. D., von Haeseler, A., & Lanfear, R. (2020). IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era. Molecular Biology and Evolution, 37(5), 1530–1534.
[Tree inference] Stamatakis, A. (2014). RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics (Oxford, England), 30(9), 1312–1313.

- Further reading
[More about meta-analysis of phylogenetic programs] Spirin, S., Sigorskikh, A., Efremov, A., Penzar, D., & Karyagina, A. (2024). PhyloBench: A benchmark for evaluating phylogenetic programs. Molecular Biology and Evolution, 41(6), msae084
[More about protein structure-based phylogenetics] Puente-Lelievre, C., Malik, A., & Douglas, J. (2025). Protein structural phylogenetics. Genome Biology and Evolution, 17(8), evaf139.

2. Reference-free, Statistical

- Presented
Felsenstein, J. (1985). Confidence limits on phylogenies: An approach using the bootstrap. Evolution; International Journal of Organic Evolution, 39(4), 783–791.
Estabrook, G. F., McMorris, F. R., & Meacham, C. A. (1985). Comparison of Undirected Phylogenetic Trees Based on Subtrees of Four Evolutionary Units. Systematic Biology, 34(2), 193–200.
Huelsenbeck, J., & Ronquist, F. (2001). MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics, 17(8), 754–755.
De Maio, N., Ly-Trong, N., Martin, S., Minh, B. Q., & Goldman, N. (2025). Assessing phylogenetic confidence at pandemic scales. Nature, 1–7.

- Further reading
[Approach based on information theory] Salichos, L., Stamatakis, A., & Rokas, A. (2014). Novel information theory-based measures for quantifying incongruence among phylogenetic trees. Molecular Biology and Evolution, 31(5), 1261–1271.
[Likelihood-ratio test] Anisimova, M., & Gascuel, O. (2006). Approximate likelihood-ratio test for branches: A fast, accurate, and powerful alternative. Systematic Biology, 55(4), 539–552.
[Recent insights on Bayesian approaches] Lemoine, F., & Gascuel, O. (2024). The Bayesian phylogenetic bootstrap and its application to short trees and branches. Molecular Biology and Evolution, 41(11), msae238.

3. Reference-free, Biological

- Presented
Dessimoz, C., & Gil, M. (2010). Phylogenetic assessment of alignments reveals neglected tree signal in gaps. Genome Biology, 11(4), R37.
Tajima, F. (1993). Simple methods for testing the molecular evolutionary clock hypothesis. Genetics, 135(2), 599–607.

- Further reading
[More about molecular clock hypothesis] Bereg, S., & Zhang, Y. (2007). Phylogenetic networks based on the molecular clock hypothesis. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 4(4), 661–667.
[Debate on applying ultrametricity on structure-based trees] Mutti, G., Ocaña-Pallarès, E., & Gabaldón, T. (2025). Newly developed structure-based methods do not outperform standard sequence-based methods for large-scale phylogenomics. Molecular Biology and Evolution, 42(7). https://doi.org/10.1093/molbev/msaf149

4. Reference-based, Statistical

- Presented
Robinson, D. F., & Foulds, L. R. (1981). Comparison of phylogenetic trees. Mathematical Biosciences, 53(1–2), 131–147.
Estabrook, G. F., McMorris, F. R., & Meacham, C. A. (1985). Comparison of Undirected Phylogenetic Trees Based on Subtrees of Four Evolutionary Units. Systematic Biology, 34(2), 193–200.
Smith, M. R. (2022). Robust analysis of phylogenetic tree space. Systematic Biology, 71(5), 1255–1270.

- Further reading
[More on the generalization RF distances] Briand, S., Dessimoz, C., El-Mabrouk, N., Lafond, M., & Lobinska, G. (2020). A generalized Robinson-Foulds distance for labeled trees. BMC Genomics, 21(Suppl 10), 779.


5. Reference-based, Biological

- Presented
Tan, G., Gil, M., Löytynoja, A. P., Goldman, N., & Dessimoz, C. (2015). Simple chained guide trees give poorer multiple sequence alignments than inferred trees in simulation and phylogenetic benchmarks. Proceedings of the National Academy of Sciences of the United States of America, 112(2), E99-100.
Moi, D., Bernard, C., Steinegger, M., Nevers, Y., Langleib, M., & Dessimoz, C. (2025). Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses. Nature Structural & Molecular Biology, 1–11.
Schoch, C. L., Ciufo, S., Domrachev, M., Hotton, C. L., Kannan, S., Khovanskaya, R., Leipe, D., Mcveigh, R., O’Neill, K., Robbertse, B., Sharma, S., Soussov, V., Sullivan, J. P., Sun, L., Turner, S., & Karsch-Mizrachi, I. (2020). NCBI Taxonomy: a comprehensive update on curation, resources and tools. Database, 2020. https://doi.org/10.1093/database/baaa062

- Further reading
[Established bacterial taxonomy] Parks, D. H., Chuvochina, M., Rinke, C., Mussig, A. J., Chaumeil, P.-A., & Hugenholtz, P. (2022). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Research, 50(D1), D785–D794.

6. More
[Machine learning in phylogenetics review] Mo, Y. K., Hahn, M. W., & Smith, M. L. (2024). Applications of machine learning in phylogenetics. Molecular Phylogenetics and Evolution, 196(108066), 108066.
[Recent approach using machine learning for MSAs] Dotan, E., Wygoda, E., Ecker, N., Alburquerque, M., Avram, O., Belinkov, Y., & Pupko, T. (2024). BetaAlign: a deep learning approach for multiple sequence alignment. Bioinformatics (Oxford, England), 41(1). https://doi.org/10.1093/bioinformatics/btaf009
[Phylogenetic assessment review regarding MSAs] Bogusz, M., & Whelan, S. (2017). Phylogenetic tree estimation with and without alignment: New distance methods and benchmarking. Systematic Biology, 66(2), 218–231.
