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Matthieu Foll

Showing results (1-10 of 79) with videos related to

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Bioinformatics (Oxford, England)|March 15, 2011
fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenariosLaurent Excoffier, Matthieu Foll
Genetics|September 11, 2008
A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspectiveMatthieu Foll, Oscar Gaggiotti
Bioinformatics (Oxford, England)|January 13, 2009
Correcting for ascertainment bias in the inference of population structureGilles Guillot, Matthieu Foll
Genetics|September 5, 2006
Identifying the environmental factors that determine the genetic structure of populationsMatthieu Foll, Oscar Gaggiotti
Translational Lung Cancer Research|February 11, 2020
Molecular studies of lung neuroendocrine neoplasms uncover new concepts and entitiesLynnette Fernandez-Cuesta, Matthieu Foll
Molecular Ecology Resources|May 14, 2011
Quantifying population structure using the F-modelOscar E Gaggiotti, Matthieu Foll
BMC Genomics|March 24, 2012
Evolutionary forces shaping genomic islands of population differentiation in humansTamara Hofer, Matthieu Foll, Laurent Excoffier
Molecular Ecology Resources|May 20, 2014
WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled dataMatthieu Foll, Hyunjin Shim, Jeffrey D Jensen
Molecular Ecology|January 9, 2016
The past, present and future of genomic scans for selectionJeffrey D Jensen, Matthieu Foll, Louis Bernatchez
Genetics|May 29, 2008
An approximate Bayesian computation approach to overcome biases that arise when using amplified fragment length polymorphism markers to study population structureMatthieu Foll, Mark A Beaumont, Oscar Gaggiotti
Pageof 8

Showing results (1-10 of 79) with videos related to

Sort By:
Pageof 8
Bioinformatics (Oxford, England)|March 15, 2011
fastsimcoal: a continuous-time coalescent simulator of genomic diversity under arbitrarily complex evolutionary scenariosLaurent Excoffier, Matthieu Foll
Genetics|September 11, 2008
A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspectiveMatthieu Foll, Oscar Gaggiotti
Bioinformatics (Oxford, England)|January 13, 2009
Correcting for ascertainment bias in the inference of population structureGilles Guillot, Matthieu Foll
Genetics|September 5, 2006
Identifying the environmental factors that determine the genetic structure of populationsMatthieu Foll, Oscar Gaggiotti
Translational Lung Cancer Research|February 11, 2020
Molecular studies of lung neuroendocrine neoplasms uncover new concepts and entitiesLynnette Fernandez-Cuesta, Matthieu Foll
Molecular Ecology Resources|May 14, 2011
Quantifying population structure using the F-modelOscar E Gaggiotti, Matthieu Foll
BMC Genomics|March 24, 2012
Evolutionary forces shaping genomic islands of population differentiation in humansTamara Hofer, Matthieu Foll, Laurent Excoffier
Molecular Ecology Resources|May 20, 2014
WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled dataMatthieu Foll, Hyunjin Shim, Jeffrey D Jensen
Molecular Ecology|January 9, 2016
The past, present and future of genomic scans for selectionJeffrey D Jensen, Matthieu Foll, Louis Bernatchez
Genetics|May 29, 2008
An approximate Bayesian computation approach to overcome biases that arise when using amplified fragment length polymorphism markers to study population structureMatthieu Foll, Mark A Beaumont, Oscar Gaggiotti
Pageof 8