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Emmanuel Paradis

dblp:55/5038 · DBLP profile ↗
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4ranked-venue papers
3as first author
0since 2021 · last 2019
0000-0003-3092-2199ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 3 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
4 papers
Bioinformatics and computational biology · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
phylogenetics
0.632019
ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R · Bioinform. 2019
ape 3.0: New tools for distance-based phylogenetics and evolutionary analysis in R · Bioinform. 2012
APE: Analyses of Phylogenetics and Evolution in R language · Bioinform. 2004
Bioinformatics and computational biology › evolutionary biology
evolutionary analysis
0.412019
ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R · Bioinform. 2019
Bioinformatics and computational biology › phylogenetics › phyloinformatics
phylogenetic analysis software
0.412019
ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R · Bioinform. 2019
Bioinformatics and computational biology › phylogenetics
phylogenetic inference
0.112012
ape 3.0: New tools for distance-based phylogenetics and evolutionary analysis in R · Bioinform. 2012
Bioinformatics and computational biology
population genetics
0.112010
pegas: an R package for population genetics with an integrated-modular approach · Bioinform. 2010
Bioinformatics and computational biology
molecular evolution
0.012004
APE: Analyses of Phylogenetics and Evolution in R language · Bioinform. 2004
Bioinformatics and computational biology › phylogenetics
phylogenetic tree analysis
0.012004
APE: Analyses of Phylogenetics and Evolution in R language · Bioinform. 2004

Methods — techniques the papers use, named apart from their topics

distance matrix methods · 0.1population genetic methods · 0.0comparative methods · 0.0
YearPublicationVenuePosition
2019 ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R
abstract
Summary: After more than fifteen years of existence, the R package ape has continuously grown its contents, and has been used by a growing community of users. The release of version 5.0 has marked a leap towards a modern software for evolutionary analyses. Efforts have been put to improve efficiency, flexibility, support for 'big data' (R's long vectors), ease of use and quality check before a new release. These changes will hopefully make ape a useful software for the study of biodiversity and evolution in a context of increasing data quantity. Availability and implementation: ape is distributed through the Comprehensive R Archive Network: http://cran.r-project.org/package=ape. Further information may be found at http://ape-package.ird.fr/.
Emmanuel Paradis, Klaus Schliep
Bioinform.1
2012 ape 3.0: New tools for distance-based phylogenetics and evolutionary analysis in R
abstract
UNLABELLED: Reflecting its continuously increasing versatility and functionality, the popularity of the ape (analysis of phylogenetics and evolution) software package has grown steadily over the years. Among its features, it has a strong distance-based component allowing the user to compute distances from aligned DNA sequences based on most methods from the literature and also build phylogenetic trees from them. However, even data generated with modern genomic approaches can fail to give rise to sufficiently reliable distance estimates. One way to overcome this problem is to exclude such estimates from data analysis giving rise to an incomplete distance data set (as opposed to a complete one). So far their analysis has been out of reach for ape. To remedy this, we have incorporated into ape several methods from the literature for phylogenetic inference from incomplete distance matrices. In addition, we have also extended ape's repertoire for phylogenetic inference from complete distances, added a new object class to efficiently encode sets of splits of taxa, and extended the functionality of some of its existing functions. AVAILABILITY: ape is distributed through the Comprehensive R Archive Network: http://cran.r-project.org/web/packages/ape/index.html Further information may be found at http://ape.mpl.ird.fr/pegas/
Andrei-Alin Popescu, Katharina T. Huber, Emmanuel Paradis
Bioinform.3
2010 pegas: an R package for population genetics with an integrated-modular approach
abstract
SUMMARY: pegas (Population and Evolutionary Genetics Analysis System) is a new package for the analysis of population genetic data. It is written in R and is integrated with two other existing R packages (ape and adegenet). pegas provides functions for standard population genetic methods, as well as low-level functions for developing new methods. The flexible and efficient graphical capabilities of R are used for plotting haplotype networks as well as for other functionalities. pegas emphasizes the need to further develop an integrated-modular approach for software dedicated to the analysis of population genetic data. AVAILABILITY: pegas is distributed through the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/pegas/index.html. Further information may be found at: http://ape.mpl.ird.fr/pegas/.
Emmanuel Paradis
Bioinform.1
2004 APE: Analyses of Phylogenetics and Evolution in R language
abstract
UNLABELLED: Analysis of Phylogenetics and Evolution (APE) is a package written in the R language for use in molecular evolution and phylogenetics. APE provides both utility functions for reading and writing data and manipulating phylogenetic trees, as well as several advanced methods for phylogenetic and evolutionary analysis (e.g. comparative and population genetic methods). APE takes advantage of the many R functions for statistics and graphics, and also provides a flexible framework for developing and implementing further statistical methods for the analysis of evolutionary processes. AVAILABILITY: The program is free and available from the official R package archive at http://cran.r-project.org/src/contrib/PACKAGES.html#ape. APE is licensed under the GNU General Public License.
Emmanuel Paradis, Julien Claude, Korbinian Strimmer
Bioinform.1