| A Diffusion-Based Approach for Simulating Forward-in-Time State-Dependent Speciation and Extinction Dynamics AC Soewongsono, MJ Landis ArXiv, 2024 | | 2024 |
| A global phylogeny of butterflies reveals their evolutionary history, ancestral hosts and biogeographic origins AY Kawahara, C Storer, APS Carvalho, DM Plotkin, FL Condamine, ... Nature ecology & evolution 7 (6), 903-913, 2023 | 50 | 2023 |
| An evolutionary insertion in the Mxra8 receptor-binding site confers resistance to alphavirus infection and pathogenesis AS Kim, O Zimmerman, JM Fox, CA Nelson, K Basore, R Zhang, L Durnell, ... Cell host & microbe 27 (3), 428-440. e9, 2020 | 38 | 2020 |
| Bayesian analysis of biogeography when the number of areas is large MJ Landis, NJ Matzke, BR Moore, JP Huelsenbeck Systematic Biology 62 (6), 789-804, 2013 | 745 | 2013 |
| Bayesian inference of admixture graphs on Native American and Arctic populations SV Nielsen, AH Vaughn, K Leppälä, MJ Landis, T Mailund, R Nielsen PLoS genetics 19 (2), e1010410, 2023 | 14 | 2023 |
| Bayesian inference of ancestral host-parasite interactions under a phylogenetic model of host repertoire evolution MP Braga, MJ Landis, S Nylin, N Janz, F Ronquist Systematic Biology 69 (6), 1149–1162, 2020 | 33 | 2020 |
| Biogeographic dating of phylogenetic divergence times using priors and processes MJ Landis The Molecular Evolutionary Clock (ed. Simon Y. H. Ho), 135-155, 2021 | 6 | 2021 |
| Biogeographic dating of speciation times using paleogeographically informed processes MJ Landis Systematic Biology 66 (2), 128-144, 2017 | 75 | 2017 |
| Cophylogenetic methods to untangle the evolutionary history of ecological interactions W Dismukes, MP Braga, DH Hembry, TA Heath, MJ Landis Annual Review of Ecology, Evolution, and Systematics 53 (1), 275-298, 2022 | 16 | 2022 |
| Deep learning and likelihood approaches for viral phylogeography converge on the same answers whether the inference model is right or wrong A Thompson, B Liebeskind, EJ Scully, M Landis Systematic Biology, syad074, 2024 | 6 | 2024 |
| Deep learning approaches to viral phylogeography are fast and as robust as likelihood methods to model misspecification A Thompson, B Liebeskind, EJ Scully, M Landis bioRxiv, 2023.02. 08.527714, 2023 | 2 | 2023 |
| Genomics expands the mammalverse NS Upham, MJ Landis Science 380 (6643), 358-359, 2023 | 4 | 2023 |
| Interdependent phenotypic and biogeographic evolution driven by biotic interactions I Quintero, MJ Landis Systematic biology 69 (4), 739-755, 2020 | 42 | 2020 |
| Joint phylogenetic estimation of geographic movements and biome shifts during the global diversification of Viburnum MJ Landis, DAR Eaton, WL Clement, B Park, EL Spriggs, PW Sweeney, ... Systematic Biology 70 (1), 67-85, 2021 | 47 | 2021 |
| Lessons learned from organizing and teaching virtual phylogenetics workshops J Barido-Sottani, JA Justison, R Borges, JM Brown, W Dismukes, ... © 2022 The Authors, 2022 | | 2022 |
| Modeling phylogenetic biome shifts on a planet with a past MJ Landis, EJ Edwards, MJ Donoghue Systematic Biology 70 (1), 86-107, 2021 | 38 | 2021 |
| Parallel power posterior analyses for fast computation of marginal likelihoods in phylogenetics S Höhna, MJ Landis, JP Huelsenbeck PeerJ 9, e12438, 2021 | 23 | 2021 |
| phyddle: software to fit phylogenetic models with deep learning MJ Landis, A Thompson https://github.com/mlandis/phyddle, 2024 | | 2024 |
| Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits MJ Landis, JG Schraiber, M Liang Systematic Biology 62 (2), 193-204, 2013 | 144 | 2013 |
| Phylogenetic Inference for Biogeographic and Quantitative Trait Evolution M Landis University of California, Berkeley, 2015 | | 2015 |
