Background: The reconstruction of the phylogenetic tree topology of four taxa is, still nowadays, one of the main challenges in phylogenetics. Its difficulties lie in considering not too restrictive evolutionary models, and correctly dealing with the long-branch attraction problem. The correct reconstruction of 4-taxon trees is crucial for making quartet-based methods work and being able to recover large phylogenies.
Methods: We adapt the well known expectation-maximization algorithm to evolutionary Markov models on phylogenetic 4-taxon trees. We then use this algorithm to estimate the substitution parameters, compute the corresponding likelihood, and to infer the most likely quartet.
Results: In this paper we consider an expectation-maximization method for maximizing the likelihood of (time nonhomogeneous) evolutionary Markov models on trees. We study its success on reconstructing 4-taxon topologies and its performance as input method in quartet-based phylogenetic reconstruction methods such as QFIT and QuartetSuite. Our results show that the method proposed here outperforms neighbor-joining and the usual (time-homogeneous continuous-time) maximum likelihood methods on 4-leaved trees with among-lineage instantaneous rate heterogeneity, and perform similarly to usual continuous-time maximum-likelihood when data satisfies the assumptions of both methods.
Conclusions: The method presented in this paper is well suited for reconstructing the topology of any number of taxa via quartet-based methods and is highly accurate, specially regarding largely divergent trees and time nonhomogeneous data.
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http://dx.doi.org/10.1186/1471-2148-14-132 | DOI Listing |
Medicina (Kaunas)
December 2024
Department of Cariology, Endodontics and Oral Pathology, School of Dental Medicine, University of Medicine and Pharmacy Iuliu Hatieganu, Str. Motilor 33, 400001 Cluj-Napoca, Romania.
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View Article and Find Full Text PDFEntropy (Basel)
December 2024
Consiglio Nazionale delle Ricerche-Istituto di Matematica Applicata e Tecnologie Informatiche, I-20133 Milano, Italy.
The probability of gas escapes from steel pipelines due to different types of corrosion is studied with real failure data from an urban gas distribution network. Both the design and maintenance of the network are considered, identifying and estimating (in a Bayesian framework) an elementary multinomial model in the first case, and a more sophisticated non-homogeneous Poisson process in the second case. Special attention is paid to the elicitation of the experts' opinions.
View Article and Find Full Text PDFMed Decis Making
January 2025
Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA.
The nonparametric sampling method is generic and can sample times to an event from any discrete (or discretizable) hazard without requiring any parametric assumption.The method is showcased with 5 commonly used distributions in discrete-event simulation models.The method produced very similar expected times to events, as well as their probability distribution, compared with analytical results.
View Article and Find Full Text PDFInterdiscip Cardiovasc Thorac Surg
December 2024
Department of Cardiovascular Surgery, University Hospital Freiburg Heart Centre, Freiburg, Germany.
Objectives: Evidence for different surveillance protocols following aortic treatment is still lacking. The aim of this study was to analyse the clinical relevance of a first follow-up visit after 6 months.
Methods: Between January 2018 and December 2019, 464 patients treated for non-emergent aortic pathologies were retrospectively analysed.
Materials (Basel)
December 2024
Department of Engineering Science, University West, SE-461 86 Trollhättan, Sweden.
Additive manufacturing (AM) methods like powder bed fusion-laser beam (PBF-LB) enable complex geometry production. However, understanding and predicting the microstructural properties of AM parts remain challenging due to the inherent non-homogeneity introduced during the manufacturing process. This study demonstrates a novel approach for 3D microstructure representation and virtual testing of non-homogeneous AM materials using 2d electron backscatter diffraction (EBSD) data.
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