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Items: 1 to 20 of 159

1.

ABC as a flexible framework to estimate demography over space and time: some cons, many pros.

Bertorelle G, Benazzo A, Mona S.

Mol Ecol. 2010 Jul;19(13):2609-25. doi: 10.1111/j.1365-294X.2010.04690.x. Epub 2010 Jun 18. Review.

PMID:
20561199
2.

ABC: a useful Bayesian tool for the analysis of population data.

Lopes JS, Beaumont MA.

Infect Genet Evol. 2010 Aug;10(6):826-33. doi: 10.1016/j.meegid.2009.10.010. Epub 2009 Oct 30.

PMID:
19879976
3.

Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation.

Cornuet JM, Santos F, Beaumont MA, Robert CP, Marin JM, Balding DJ, Guillemaud T, Estoup A.

Bioinformatics. 2008 Dec 1;24(23):2713-9. doi: 10.1093/bioinformatics/btn514. Epub 2008 Oct 7.

4.

Approximate bayesian computation without summary statistics: the case of admixture.

Sousa VC, Fritz M, Beaumont MA, Chikhi L.

Genetics. 2009 Apr;181(4):1507-19. doi: 10.1534/genetics.108.098129. Epub 2009 Feb 2.

5.
6.

Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0).

Cornuet JM, Ravigné V, Estoup A.

BMC Bioinformatics. 2010 Jul 28;11:401. doi: 10.1186/1471-2105-11-401.

7.
8.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

Wegmann D, Leuenberger C, Neuenschwander S, Excoffier L.

BMC Bioinformatics. 2010 Mar 4;11:116. doi: 10.1186/1471-2105-11-116.

9.

Distinguishing between population bottleneck and population subdivision by a Bayesian model choice procedure.

Peter BM, Wegmann D, Excoffier L.

Mol Ecol. 2010 Nov;19(21):4648-60. doi: 10.1111/j.1365-294X.2010.04783.x. Epub 2010 Aug 23.

PMID:
20735743
10.

Genetic analysis of complex demographic scenarios: spatially expanding populations of the cane toad, Bufo marinus.

Estoup A, Beaumont M, Sennedot F, Moritz C, Cornuet JM.

Evolution. 2004 Sep;58(9):2021-36.

PMID:
15521459
11.

An approximate Bayesian computation approach to overcome biases that arise when using amplified fragment length polymorphism markers to study population structure.

Foll M, Beaumont MA, Gaggiotti O.

Genetics. 2008 Jun;179(2):927-39. doi: 10.1534/genetics.107.084541. Epub 2008 May 27.

12.

Approximate Bayesian Computation (ABC) in practice.

Csilléry K, Blum MG, Gaggiotti OE, François O.

Trends Ecol Evol. 2010 Jul;25(7):410-8. doi: 10.1016/j.tree.2010.04.001. Epub 2010 May 18. Review.

PMID:
20488578
13.

Lack of confidence in approximate Bayesian computation model choice.

Robert CP, Cornuet JM, Marin JM, Pillai NS.

Proc Natl Acad Sci U S A. 2011 Sep 13;108(37):15112-7. doi: 10.1073/pnas.1102900108. Epub 2011 Aug 29.

14.

Data cloning: easy maximum likelihood estimation for complex ecological models using Bayesian Markov chain Monte Carlo methods.

Lele SR, Dennis B, Lutscher F.

Ecol Lett. 2007 Jul;10(7):551-63. Erratum in: Ecol Lett. 2007 Sep;10(9):866.

PMID:
17542934
15.

Automating approximate Bayesian computation by local linear regression.

Thornton KR.

BMC Genet. 2009 Jul 7;10:35. doi: 10.1186/1471-2156-10-35.

16.

How vague is vague? A simulation study of the impact of the use of vague prior distributions in MCMC using WinBUGS.

Lambert PC, Sutton AJ, Burton PR, Abrams KR, Jones DR.

Stat Med. 2005 Aug 15;24(15):2401-28.

PMID:
16015676
17.

BEAST: Bayesian evolutionary analysis by sampling trees.

Drummond AJ, Rambaut A.

BMC Evol Biol. 2007 Nov 8;7:214.

18.
19.

pIPHULA--parallel inference of population parameters using a likelihood approach.

Schmidt HA, von Haeseler A, Buschbom J.

Bioinformatics. 2007 Oct 1;23(19):2636-7. Epub 2007 Aug 12.

20.

On the use of kernel approximate Bayesian computation to infer population history.

Nakagome S.

Genes Genet Syst. 2015;90(3):153-62. doi: 10.1266/ggs.90.153. Review.

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