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Alexandre Dehne-Garcia

dblp:97/3018 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1

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
1 paper
Bioinformatics and computational biology · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
approximate bayesian computation
0.212014
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data · Bioinform. 2014
Bioinformatics and computational biology › population genetics › population parameter estimation
demographic inference
0.212014
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data · Bioinform. 2014
Bioinformatics and computational biology
population genetics
0.212014
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data · Bioinform. 2014

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

linear discriminant analysis · 0.2bayesian model choice · 0.2approximate bayesian computation · 0.2
YearPublicationVenuePosition
2014 DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data
abstract
MOTIVATION: DIYABC is a software package for a comprehensive analysis of population history using approximate Bayesian computation on DNA polymorphism data. Version 2.0 implements a number of new features and analytical methods. It allows (i) the analysis of single nucleotide polymorphism data at large number of loci, apart from microsatellite and DNA sequence data, (ii) efficient Bayesian model choice using linear discriminant analysis on summary statistics and (iii) the serial launching of multiple post-processing analyses. DIYABC v2.0 also includes a user-friendly graphical interface with various new options. It can be run on three operating systems: GNU/Linux, Microsoft Windows and Apple Os X. AVAILABILITY: Freely available with a detailed notice document and example projects to academic users at http://www1.montpellier.inra.fr/CBGP/diyabc CONTACT: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.
Jean-Marie Cornuet, Pierre Pudlo, Julien Veyssier, Alexandre Dehne-Garcia, Mathieu Gautier, Raphaël Leblois, Jean-Michel Marin, Arnaud Estoup
Bioinform.4