about
Lack of confidence in approximate Bayesian computation model choiceDIYABC v2.0: a software to make approximate Bayesian computation inferences about population history using single nucleotide polymorphism, DNA sequence and microsatellite data.Deciphering the Routes of invasion of Drosophila suzukii by Means of ABC Random ForestInferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.Unraveling cell type-specific and reprogrammable human replication origin signatures associated with G-quadruplex consensus motifs.Reliable ABC model choice via random forests.Probing instructions for expression regulation in gene nucleotide compositions.Approximate Bayesian computational methods
P50
Q24635950-1BAD8900-116F-4645-A30C-8F7DD17C1102Q30726102-33852705-B782-49ED-8124-F244C725F341Q33590740-6C79F340-CEA1-41D7-90A2-4716F3BD0C99Q37090724-C4120D7D-DCFE-43BF-A885-0C260110771DQ39321886-FFB4ED68-53B0-443B-8CD9-378F3B4A06C7Q40295315-A73C2475-9A12-460B-AFB9-D5555BAAA11FQ47224226-E415324E-8AEB-491E-A140-F8A0A5597EE1Q56689494-76CC211A-3B52-4094-9FF2-695DEF476EF1
P50
description
onderzoeker
@nl
researcher
@en
հետազոտող
@hy
name
Jean-Michel Marin
@ast
Jean-Michel Marin
@en
Jean-Michel Marin
@es
Jean-Michel Marin
@nl
Jean-Michel Marin
@sl
type
label
Jean-Michel Marin
@ast
Jean-Michel Marin
@en
Jean-Michel Marin
@es
Jean-Michel Marin
@nl
Jean-Michel Marin
@sl
prefLabel
Jean-Michel Marin
@ast
Jean-Michel Marin
@en
Jean-Michel Marin
@es
Jean-Michel Marin
@nl
Jean-Michel Marin
@sl
P106
P2456
P31
P496
0000-0001-7451-9719