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Items: 1 to 50 of 90

1.

Genome-Wide Association Study (GWAS) identified novel candidate loci affecting wood formation in Norway spruce.

Baison J, Vidalis A, Zhou L, Chen ZQ, Li Z, Sillanpää MJ, Bernhardsson C, Scofield D, Forsberg N, Grahn T, Olsson L, Karlsson B, Wu H, Ingvarsson PK, Lundqvist SO, Niittylä T, García-Gil MR.

Plant J. 2019 Jun 5. doi: 10.1111/tpj.14429. [Epub ahead of print]

PMID:
31166032
2.

A Gaussian process model and Bayesian variable selection for mapping function-valued quantitative traits with incomplete phenotypic data.

Vanhatalo J, Li Z, Sillanpää MJ.

Bioinformatics. 2019 Mar 8. pii: btz164. doi: 10.1093/bioinformatics/btz164. [Epub ahead of print]

PMID:
30850830
3.

Mobile road weather sensor calibration by sensor fusion and linear mixed models.

Lovén L, Karsisto V, Järvinen H, Sillanpää MJ, Leppänen T, Peltonen E, Pirttikangas S, Riekki J.

PLoS One. 2019 Feb 7;14(2):e0211702. doi: 10.1371/journal.pone.0211702. eCollection 2019.

4.

Two novel genomic regions associated with fearfulness in dogs overlap human neuropsychiatric loci.

Sarviaho R, Hakosalo O, Tiira K, Sulkama S, Salmela E, Hytönen MK, Sillanpää MJ, Lohi H.

Transl Psychiatry. 2019 Jan 17;9(1):18. doi: 10.1038/s41398-018-0361-x.

5.

Stochastic search variable selection based on two mixture components and continuous-scale weighting.

Rinta-Aho MJ, Sillanpää MJ.

Biom J. 2019 May;61(3):729-746. doi: 10.1002/bimj.201800118. Epub 2018 Dec 10.

PMID:
30537402
6.

Analysis of phenotypic- and Estimated Breeding Values (EBV) to dissect the genetic architecture of complex traits in a Scots pine three-generation pedigree design.

Calleja-Rodriguez A, Li Z, Hallingbäck HR, Sillanpää MJ, Wu HX, Abrahamsson S, García-Gil MR.

J Theor Biol. 2019 Feb 7;462:283-292. doi: 10.1016/j.jtbi.2018.11.007. Epub 2018 Nov 10.

7.

Estimating multilevel regional variation in excess mortality of cancer patients using integrated nested Laplace approximation.

Seppä K, Rue H, Hakulinen T, Läärä E, Sillanpää MJ, Pitkäniemi J.

Stat Med. 2019 Feb 28;38(5):778-791. doi: 10.1002/sim.8010. Epub 2018 Oct 17.

PMID:
30334278
8.

Impact of residual covariance structures on genomic prediction ability in multi-environment trials.

Mathew B, Léon J, Sillanpää MJ.

PLoS One. 2018 Jul 20;13(7):e0201181. doi: 10.1371/journal.pone.0201181. eCollection 2018.

9.

Detection of Epistasis for Flowering Time Using Bayesian Multilocus Estimation in a Barley MAGIC Population.

Mathew B, Léon J, Sannemann W, Sillanpää MJ.

Genetics. 2018 Feb;208(2):525-536. doi: 10.1534/genetics.117.300546. Epub 2017 Dec 18.

10.

A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction.

Mathew B, Léon J, Sillanpää MJ.

Heredity (Edinb). 2018 Apr;120(4):356-368. doi: 10.1038/s41437-017-0023-4. Epub 2017 Dec 14.

11.

ACEt: An R Package for Estimating Dynamic Heritability and Comparing Twin Models.

He L, Pitkäniemi J, Silventoinen K, Sillanpää MJ.

Behav Genet. 2017 Nov;47(6):620-641. doi: 10.1007/s10519-017-9866-y. Epub 2017 Sep 6.

PMID:
28879484
12.

Genetic heterogeneity underlying variation in a locally adaptive clinal trait in Pinus sylvestris revealed by a Bayesian multipopulation analysis.

Kujala ST, Knürr T, Kärkkäinen K, Neale DB, Sillanpää MJ, Savolainen O.

Heredity (Edinb). 2017 May;118(5):413-423. doi: 10.1038/hdy.2016.115. Epub 2016 Nov 30.

13.

Prioritizing covariates in the planning of future studies in the meta-analytic framework.

Karvanen J, Sillanpää MJ.

Biom J. 2017 Jan;59(1):110-125. doi: 10.1002/bimj.201600067. Epub 2016 Oct 14.

PMID:
27740692
14.

Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.

He L, Sillanpää MJ, Silventoinen K, Kaprio J, Pitkäniemi J.

Genetics. 2016 Apr;202(4):1313-28. doi: 10.1534/genetics.115.183905. Epub 2016 Feb 11.

15.

Use of Wishart Prior and Simple Extensions for Sparse Precision Matrix Estimation.

Kuismin M, Sillanpää MJ.

PLoS One. 2016 Feb 1;11(2):e0148171. doi: 10.1371/journal.pone.0148171. eCollection 2016.

16.

Reparametrization-based estimation of genetic parameters in multi-trait animal model using Integrated Nested Laplace Approximation.

Mathew B, Holand AM, Koistinen P, Léon J, Sillanpää MJ.

Theor Appl Genet. 2016 Feb;129(2):215-25. doi: 10.1007/s00122-015-2622-x. Epub 2015 Nov 18.

17.

Dynamic Quantitative Trait Locus Analysis of Plant Phenomic Data.

Li Z, Sillanpää MJ.

Trends Plant Sci. 2015 Dec;20(12):822-833. doi: 10.1016/j.tplants.2015.08.012. Epub 2015 Oct 5. Review.

PMID:
26482958
18.

An Efficient Genome-Wide Multilocus Epistasis Search.

Kärkkäinen HP, Li Z, Sillanpää MJ.

Genetics. 2015 Nov;201(3):865-70. doi: 10.1534/genetics.115.182444. Epub 2015 Sep 23.

19.

A robust multiple-locus method for quantitative trait locus analysis of non-normally distributed multiple traits.

Li Z, Möttönen J, Sillanpää MJ.

Heredity (Edinb). 2015 Dec;115(6):556-64. doi: 10.1038/hdy.2015.61. Epub 2015 Jul 15.

20.

Prediction of complex human diseases from pathway-focused candidate markers by joint estimation of marker effects: case of chronic fatigue syndrome.

Bhattacharjee M, Rajeevan MS, Sillanpää MJ.

Hum Genomics. 2015 Jun 11;9:8. doi: 10.1186/s40246-015-0030-6.

21.

Efficient use of systems mapping without expert knowledge: Comment on "Mapping complex traits as a dynamic system" by L. Sun and R. Wu.

Li Z, Sillanpää MJ.

Phys Life Rev. 2015 Jun;13:192-3. doi: 10.1016/j.plrev.2015.04.001. Epub 2015 Apr 3. No abstract available.

PMID:
25866353
22.

Bayesian LASSO, scale space and decision making in association genetics.

Pasanen L, Holmström L, Sillanpää MJ.

PLoS One. 2015 Apr 9;10(4):e0120017. doi: 10.1371/journal.pone.0120017. eCollection 2015.

23.

Hierarchical Bayesian model for rare variant association analysis integrating genotype uncertainty in human sequence data.

He L, Pitkäniemi J, Sarin AP, Salomaa V, Sillanpää MJ, Ripatti S.

Genet Epidemiol. 2015 Feb;39(2):89-100. doi: 10.1002/gepi.21871. Epub 2014 Nov 13.

PMID:
25395270
24.

Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.

Li Z, Hallingbäck HR, Abrahamsson S, Fries A, Gull BA, Sillanpää MJ, García-Gil MR.

G3 (Bethesda). 2014 Oct 9;4(12):2365-79. doi: 10.1534/g3.114.014068.

25.

Use of synteny to identify candidate genes underlying QTL controlling stomatal traits in faba bean (Vicia faba L.).

Khazaei H, O'Sullivan DM, Sillanpää MJ, Stoddard FL.

Theor Appl Genet. 2014 Nov;127(11):2371-85. doi: 10.1007/s00122-014-2383-y. Epub 2014 Sep 4.

PMID:
25186169
26.

Bayesian latent variable collapsing model for detecting rare variant interaction effect in twin study.

He L, Sillanpää MJ, Ripatti S, Pitkäniemi J.

Genet Epidemiol. 2014 May;38(4):310-24. doi: 10.1002/gepi.21804. Epub 2014 Apr 9.

PMID:
24719390
27.

Using the unified relationship matrix adjusted by breed-wise allele frequencies in genomic evaluation of a multibreed population.

Makgahlela ML, Strandén I, Nielsen US, Sillanpää MJ, Mäntysaari EA.

J Dairy Sci. 2014 Feb;97(2):1117-27. doi: 10.3168/jds.2013-7167. Epub 2013 Dec 15.

28.

Combined linkage disequilibrium and linkage mapping: Bayesian multilocus approach.

Pikkuhookana P, Sillanpää MJ.

Heredity (Edinb). 2014 Mar;112(3):351-60. doi: 10.1038/hdy.2013.111. Epub 2013 Nov 20.

29.

Impact of prior specifications in a shrinkage-inducing Bayesian model for quantitative trait mapping and genomic prediction.

Knürr T, Läärä E, Sillanpää MJ.

Genet Sel Evol. 2013 Jul 8;45:24. doi: 10.1186/1297-9686-45-24.

30.

Fast genomic predictions via Bayesian G-BLUP and multilocus models of threshold traits including censored Gaussian data.

Kärkkäinen HP, Sillanpää MJ.

G3 (Bethesda). 2013 Sep 4;3(9):1511-23. doi: 10.1534/g3.113.007096.

31.

A Bayesian nonparametric approach for mapping dynamic quantitative traits.

Li Z, Sillanpää MJ.

Genetics. 2013 Aug;194(4):997-1016. doi: 10.1534/genetics.113.152736. Epub 2013 Jun 14.

32.

The estimation of genomic relationships using breedwise allele frequencies among animals in multibreed populations.

Makgahlela ML, Strandén I, Nielsen US, Sillanpää MJ, Mäntysaari EA.

J Dairy Sci. 2013 Aug;96(8):5364-75. doi: 10.3168/jds.2012-6523. Epub 2013 Jun 13.

33.

Genetic parameters for claw health and feet and leg conformation traits in Finnish Ayrshire cows.

Häggman J, Juga J, Sillanpää MJ, Thompson R.

J Anim Breed Genet. 2013 Apr;130(2):89-97. doi: 10.1111/j.1439-0388.2012.01007.x. Epub 2012 May 15.

PMID:
23496009
34.

Across breed multi-trait random regression genomic predictions in the Nordic Red dairy cattle.

Makgahlela ML, Mäntysaari EA, Strandén I, Koivula M, Nielsen US, Sillanpää MJ, Juga J.

J Anim Breed Genet. 2013 Feb;130(1):10-9. doi: 10.1111/j.1439-0388.2012.01017.x. Epub 2012 Jul 19.

PMID:
23317061
35.

Associations between variation in CHRNA5-CHRNA3-CHRNB4, body mass index and blood pressure in the Northern Finland Birth Cohort 1966.

Kaakinen M, Ducci F, Sillanpää MJ, Läärä E, Järvelin MR.

PLoS One. 2012;7(9):e46557. doi: 10.1371/journal.pone.0046557. Epub 2012 Sep 27.

36.

A decision rule for quantitative trait locus detection under the extended Bayesian LASSO model.

Mutshinda CM, Sillanpää MJ.

Genetics. 2012 Dec;192(4):1483-91. doi: 10.1534/genetics.111.130278. Epub 2012 Sep 14.

37.

Robustness of Bayesian multilocus association models to cryptic relatedness.

Kärkkāinen HP, Sillanpää MJ.

Ann Hum Genet. 2012 Nov;76(6):510-23. doi: 10.1111/j.1469-1809.2012.00729.x. Epub 2012 Sep 12. Erratum in: Ann Hum Genet. 2013 May;77(3):275.

38.

Swift block-updating EM and pseudo-EM procedures for Bayesian shrinkage analysis of quantitative trait loci.

Mutshinda CM, Sillanpää MJ.

Theor Appl Genet. 2012 Nov;125(7):1575-87. doi: 10.1007/s00122-012-1936-1. Epub 2012 Jul 24.

PMID:
22824967
39.

Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters.

Mathew B, Bauer AM, Koistinen P, Reetz TC, Léon J, Sillanpää MJ.

Heredity (Edinb). 2012 Oct;109(4):235-45. doi: 10.1038/hdy.2012.35. Epub 2012 Jul 18.

40.

A hierarchical bayesian approach to multi-trait clinical quantitative trait locus modeling.

Mutshinda CM, Noykova N, Sillanpää MJ.

Front Genet. 2012 Jun 6;3:97. doi: 10.3389/fgene.2012.00097. eCollection 2012.

41.

Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection.

Li Z, Sillanpää MJ.

Theor Appl Genet. 2012 Aug;125(3):419-35. doi: 10.1007/s00122-012-1892-9. Epub 2012 May 24. Review.

PMID:
22622521
42.

Back to basics for Bayesian model building in genomic selection.

Kärkkäinen HP, Sillanpää MJ.

Genetics. 2012 Jul;191(3):969-87. doi: 10.1534/genetics.112.139014. Epub 2012 May 2.

43.

A bayesian mixed regression based prediction of quantitative traits from molecular marker and gene expression data.

Bhattacharjee M, Sillanpää MJ.

PLoS One. 2011;6(11):e26959. doi: 10.1371/journal.pone.0026959. Epub 2011 Nov 7.

44.

Estimation of quantitative trait locus effects with epistasis by variational Bayes algorithms.

Li Z, Sillanpää MJ.

Genetics. 2012 Jan;190(1):231-49. doi: 10.1534/genetics.111.134866. Epub 2011 Oct 31.

45.

Simultaneous estimation of multiple quantitative trait loci and growth curve parameters through hierarchical Bayesian modeling.

Sillanpää MJ, Pikkuhookana P, Abrahamsson S, Knürr T, Fries A, Lerceteau E, Waldmann P, García-Gil MR.

Heredity (Edinb). 2012 Feb;108(2):134-46. doi: 10.1038/hdy.2011.56. Epub 2011 Jul 27.

46.

Genetic analysis of complex traits via Bayesian variable selection: the utility of a mixture of uniform priors.

Knürr T, Läärä E, Sillanpää MJ.

Genet Res (Camb). 2011 Aug;93(4):303-18. doi: 10.1017/S0016672311000164. Epub 2011 Jul 18.

PMID:
21767461
47.

Bayesian shrinkage analysis of QTLs under shape-adaptive shrinkage priors, and accurate re-estimation of genetic effects.

Mutshinda CM, Sillanpää MJ.

Heredity (Edinb). 2011 Oct;107(5):405-12. doi: 10.1038/hdy.2011.37. Epub 2011 Jun 29.

48.

On statistical methods for estimating heritability in wild populations.

Sillanpää MJ.

Mol Ecol. 2011 Apr;20(7):1324-32. doi: 10.1111/j.1365-294X.2011.05021.x. Epub 2011 Feb 17.

PMID:
21426431
49.

Estimating haplotype frequencies by combining data from large DNA pools with database information.

Gasbarra D, Kulathinal S, Pirinen M, Sillanpää MJ.

IEEE/ACM Trans Comput Biol Bioinform. 2011 Jan-Mar;8(1):36-44. doi: 10.1109/TCBB.2009.71.

PMID:
21071795
50.

Extended Bayesian LASSO for multiple quantitative trait loci mapping and unobserved phenotype prediction.

Mutshinda CM, Sillanpää MJ.

Genetics. 2010 Nov;186(3):1067-75. doi: 10.1534/genetics.110.119586. Epub 2010 Aug 30.

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