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Proceedings of the National Academy of Sciences of the United States of America
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August 31, 2011
Lack of confidence in approximate Bayesian computation model choice
Christian P Robert, Jean-Marie Cornuet, Jean-Michel Marin, et al.
Bioinformatics (Oxford, England)
|
October 16, 2018
ABC random forests for Bayesian parameter inference
Louis Raynal, Jean-Michel Marin, Pierre Pudlo, et al.
Bioinformatics (Oxford, England)
|
November 22, 2015
Reliable ABC model choice via random forests
Pierre Pudlo, Jean-Michel Marin, Arnaud Estoup, et al.
Genome Biology
|
July 10, 2024
TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors
Raphaël Romero, Christophe Menichelli, Christophe Vroland, et al.
Molecular Ecology
|
October 1, 2020
A young age of subspecific divergence in the desert locust inferred by ABC random forest
Marie-Pierre Chapuis, Louis Raynal, Christophe Plantamp, et al.
Molecular Ecology Resources
|
May 11, 2012
Estimation of demo-genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics
Arnaud Estoup, Eric Lombaert, Jean-Michel Marin, et al.
Plos Computational Biology
|
January 3, 2018
Probing instructions for expression regulation in gene nucleotide compositions
Chloé Bessière, May Taha, Florent Petitprez, et al.
Nature Structural & Molecular Biology
|
July 4, 2012
Unraveling cell type-specific and reprogrammable human replication origin signatures associated with G-quadruplex consensus motifs
Emilie Besnard, Amélie Babled, Laure Lapasset, et al.
Molecular Ecology Resources
|
May 5, 2021
Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest
François-David Collin, Ghislain Durif, Louis Raynal, et al.
Bioinformatics (Oxford, England)
|
January 7, 2014
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data
Jean-Marie Cornuet, Pierre Pudlo, Julien Veyssier, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Proceedings of the National Academy of Sciences of the United States of America
|
August 31, 2011
Lack of confidence in approximate Bayesian computation model choice
Christian P Robert, Jean-Marie Cornuet, Jean-Michel Marin, et al.
Bioinformatics (Oxford, England)
|
October 16, 2018
ABC random forests for Bayesian parameter inference
Louis Raynal, Jean-Michel Marin, Pierre Pudlo, et al.
Bioinformatics (Oxford, England)
|
November 22, 2015
Reliable ABC model choice via random forests
Pierre Pudlo, Jean-Michel Marin, Arnaud Estoup, et al.
Genome Biology
|
July 10, 2024
TFscope: systematic analysis of the sequence features involved in the binding preferences of transcription factors
Raphaël Romero, Christophe Menichelli, Christophe Vroland, et al.
Molecular Ecology
|
October 1, 2020
A young age of subspecific divergence in the desert locust inferred by ABC random forest
Marie-Pierre Chapuis, Louis Raynal, Christophe Plantamp, et al.
Molecular Ecology Resources
|
May 11, 2012
Estimation of demo-genetic model probabilities with Approximate Bayesian Computation using linear discriminant analysis on summary statistics
Arnaud Estoup, Eric Lombaert, Jean-Michel Marin, et al.
Plos Computational Biology
|
January 3, 2018
Probing instructions for expression regulation in gene nucleotide compositions
Chloé Bessière, May Taha, Florent Petitprez, et al.
Nature Structural & Molecular Biology
|
July 4, 2012
Unraveling cell type-specific and reprogrammable human replication origin signatures associated with G-quadruplex consensus motifs
Emilie Besnard, Amélie Babled, Laure Lapasset, et al.
Molecular Ecology Resources
|
May 5, 2021
Extending approximate Bayesian computation with supervised machine learning to infer demographic history from genetic polymorphisms using DIYABC Random Forest
François-David Collin, Ghislain Durif, Louis Raynal, et al.
Bioinformatics (Oxford, England)
|
January 7, 2014
DIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data
Jean-Marie Cornuet, Pierre Pudlo, Julien Veyssier, et al.
Page
of 2