Marta Casanellas

dblp:123/6233 · DBLP profile ↗
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4ranked-venue papers
2as first author
2since 2021 · last 2021
0000-0002-1724-8358ORCID · verified

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Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author · 1 since 2021Artificial intelligence and machine learning · 1Theory of computation · 1 · 1 first-author · 1 since 2021
YearPublicationVenuePosition
2021 Distance to the stochastic part of phylogenetic varieties
Marta Casanellas, Jesús Fernández-Sánchez, Marina Garrote-López
J. Symb. Comput.1
2021 SAQ: Semi-Algebraic Quartet Reconstruction
abstract
We present the phylogenetic quartet reconstruction method SAQ (Semi-Algebraic Quartet reconstruction). SAQ is consistent with the most general Markov model of nucleotide substitution and, in particular, it allows for rate heterogeneity across lineages. Based on the algebraic and semi-algebraic description of distributions that arise from the general Markov model on a quartet, the method outputs normalized weights for the three trivalent quartets (which can be used as input of quartet-based methods). We show that SAQ is a highly competitive method that outperforms most of the well known reconstruction methods on data simulated under the general Markov model on 4-taxon trees. Moreover, it also achieves a high performance on data that violates the underlying assumptions.
Marta Casanellas, Jesús Fernández-Sánchez, Marina Garrote-López
IEEE ACM Trans. Comput. Biol. Bioinform.1
2018 A new method of moments for latent variable models
Matteo Ruffini, Marta Casanellas, Ricard Gavaldà
Mach. Learn.2
2012 GenNon-h: Generating multiple sequence alignments on nonhomogeneous phylogenetic trees
abstract
BACKGROUND: A number of software packages are available to generate DNA multiple sequence alignments (MSAs) evolved under continuous-time Markov processes on phylogenetic trees. On the other hand, methods of simulating the DNA MSA directly from the transition matrices do not exist. Moreover, existing software restricts to the time-reversible models and it is not optimized to generate nonhomogeneous data (i.e. placing distinct substitution rates at different lineages). RESULTS: We present the first package designed to generate MSAs evolving under discrete-time Markov processes on phylogenetic trees, directly from probability substitution matrices. Based on the input model and a phylogenetic tree in the Newick format (with branch lengths measured as the expected number of substitutions per site), the algorithm produces DNA alignments of desired length. GenNon-h is publicly available for download. CONCLUSION: The software presented here is an efficient tool to generate DNA MSAs on a given phylogenetic tree. GenNon-h provides the user with the nonstationary or nonhomogeneous phylogenetic data that is well suited for testing complex biological hypotheses, exploring the limits of the reconstruction algorithms and their robustness to such models.
Anna M. Kedzierska, Marta Casanellas
BMC Bioinform.2