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1701 Publications visible to you, out of a total of 1701

Abstract

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Authors: Aksel Alpay, Vincent Heuveline

Date Published: 8th Apr 2024

Publication Type: Journal

Abstract

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Authors: Luigi Crisci, Lorenzo Carpentieri, Peter Thoman, Aksel Alpay, Vincent Heuveline, Biagio Cosenza

Date Published: 8th Apr 2024

Publication Type: Journal

Abstract (Expand)

In this work, we present two distinct applications of predictive modeling within the domain of phylogenetic inference and placement. Phylogenetic placements aim to place new entities into a given phylogenetic tree. While there exist efficient implementations for producing phylogenetic placements, the underlying reasons why particular placements are more difficult to perform than others are unknown. In the first use case, we focus on the prediction of the difficulty of those phylogenetic placements. We developed Bold Assertor of Difficulty (BAD). BAD can predict the placement difficulty between 0 (easy) and 1 (hard) with high accuracy. On a set of 3000 metagenomic placements, we obtain a mean absolute error of 0.13. BAD can help biologists understand the challenges associated with placing specific sequences into a reference phylogeny during metagenomic studies based on SHapley Additive exPlanations (SHAP) explanations. Estimating the statistical robustness of the inferred phylogenetic tree constitutes an integral part of most phylogenetic analyses. Commonly, one computes and assigns a branch support value to each inner branch of the inferred phylogeny. The most widely used method for calculating branch support on trees inferred under maximum likelihood is the Standard, non parametric Felsenstein Bootstrap Support (SBS). The SBS method is computationally costly, leading to the development of alternative approaches such as Rapid Bootstrap and UltraFast Bootstrap 2 (UFBoot2). The second use case of this work is concerned with the fast machine learning-based approxi mation of those SBS values. Our SBS predictor, Educated Bootstrap Guesser (EBG), is on average 9.4 (𝜎 = 5.5) times faster than the major competitor UFBoot2 and provides an SBS estimate with a median absolute error of 5 when predicting SBS values between 0 and 10

Authors: Julius Wiegert, Julia Haag, Dimitri Höhler, Alexandros Stamatakis

Date Published: 7th Apr 2024

Publication Type: Master's Thesis

Abstract (Expand)

Despite tremendous efforts in the past decades, relationships among main avian lineages remain heavily debated without a clear resolution. Discrepancies have been attributed to diversity of species sampled, phylogenetic method, and the choice of genomic regions 1–3. Here, we address these issues by analyzing genomes of 363 bird species 4 (218 taxonomic families, 92% of total). Using intergenic regions and coalescent methods, we present a well-supported tree but also a remarkable degree of discordance. The tree confirms that Neoaves experienced rapid radiation at or near the Cretaceous–Paleogene (K–Pg) boundary. Sufficient loci rather than extensive taxon sampling were more effective in resolving difficult nodes. Remaining recalcitrant nodes involve species that challenge modeling due to extreme GC content, variable substitution rates, incomplete lineage sorting, or complex evolutionary events such as ancient hybridization. Assessment of the impacts of different genomic partitions showed high heterogeneity across the genome. We discovered sharp increases in effective population size, substitution rates, and relative brain size following the K–Pg extinction event, supporting the hypothesis that emerging ecological opportunities catalyzed the diversification of modern birds. The resulting phylogenetic estimate offers novel insights into the rapid radiation of modern birds and provides a taxon-rich backbone tree for future comparative studies.

Authors: Josefin Stiller, Shaohong Feng, Al-Aabid Chowdhury, Iker Rivas-González, David A. Duchêne, Qi Fang, Yuan Deng, Alexey Kozlov, Alexandros Stamatakis, Santiago Claramunt, Jacqueline M. T. Nguyen, Simon Y. W. Ho, Brant C. Faircloth, Julia Haag, Peter Houde, Joel Cracraft, Metin Balaban, Uyen Mai, Guangji Chen, Rongsheng Gao, Chengran Zhou, Yulong Xie, Zijian Huang, Zhen Cao, Zhi Yan, Huw A. Ogilvie, Luay Nakhleh, Bent Lindow, Benoit Morel, Jon Fjeldså, Peter A. Hosner, Rute R. da Fonseca, Bent Petersen, Joseph A. Tobias, Tamás Székely, Jonathan David Kennedy, Andrew Hart Reeve, Andras Liker, Martin Stervander, Agostinho Antunes, Dieter Thomas Tietze, Mads Bertelsen, Fumin Lei, Carsten Rahbek, Gary R. Graves, Mikkel H. Schierup, Tandy Warnow, Edward L. Braun, M. Thomas P. Gilbert, Erich D. Jarvis, Siavash Mirarab, Guojie Zhang

Date Published: 1st Apr 2024

Publication Type: Journal

Abstract

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Authors: Philip Weidner, Daniel Saar, Michaela Söhn, Torsten Schroeder, Yanxiong Yu, Frank G. Zöllner, Norbert Ponelies, Xiaobo Zhou, André Zwicky, Florian N. Rohrbacher, Vijaya R. Pattabiraman, Matthias Tanriver, Alexander Bauer, Hazem Ahmed, Simon M. Ametamey, Philipp Riffel, Rony Seger, Jeffrey W. Bode, Rebecca C. Wade, Matthias P.A. Ebert, Birthe B. Kragelund, Elke Burgermeister

Date Published: 1st Apr 2024

Publication Type: Journal

Abstract

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Authors: Alexandra Kozyreva, Javier Morán-Fraile, Alexander Holas, Vincent A. Bronner, Friedrich K. Röpke, Nikolay Pavlyuk, Alexey Mironov, Dmitry Tsvetkov

Date Published: 1st Apr 2024

Publication Type: Journal

Abstract

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Authors: A.N. Vantyghem, T.J. Galvin, B. Sebastian, C.P. O’Dea, Y.A. Gordon, M. Boyce, L. Rudnick, K. Polsterer, H. Andernach, M. Dionyssiou, P. Venkataraman, R. Norris, S.A. Baum, X.R. Wang, M. Huynh

Date Published: 1st Apr 2024

Publication Type: Journal

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