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Olivier Gascuel

Researcher at Centre national de la recherche scientifique

Publications -  182
Citations -  61205

Olivier Gascuel is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Tree (data structure) & Phylogenetic tree. The author has an hindex of 44, co-authored 173 publications receiving 53994 citations. Previous affiliations of Olivier Gascuel include Pasteur Institute & University of Montpellier.

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A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

TL;DR: This work has used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches.
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New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0

TL;DR: A new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves and a new test to assess the support of the data for internal branches of a phylogeny are introduced.
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SeaView Version 4: A Multiplatform Graphical User Interface for Sequence Alignment and Phylogenetic Tree Building

TL;DR: SeaView version 4 combines all the functions of the widely used programs SeaView and Phylo_win, and expands them by adding network access to sequence databases, alignment with arbitrary algorithm, maximum-likelihood tree building with PhyML, and display, printing, and copy-to-clipboard of rooted or unrooted, binary or multifurcating phylogenetic trees.
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Phylogeny.fr: robust phylogenetic analysis for the non-specialist

TL;DR: The Phylogeny.fr platform transparently chains programs to automatically perform phylogenetic analyses and can also meet the needs of specialists; the first ones will find up-to-date tools chained in a phylogeny pipeline to analyze their data in a simple and robust way, while the specialists will be able to easily build and run sophisticated analyses.
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An Improved General Amino Acid Replacement Matrix

TL;DR: This method further refine this method by incorporating the variability of evolutionary rates across sites in the matrix estimation and using a much larger and diverse database than BRKALN, which was used to estimate WAG.