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Items: 1 to 50 of 64

1.

Mixture cure models with time-varying and multilevel frailties for recurrent event data.

Tawiah R, McLachlan GJ, Ng SK.

Stat Methods Med Res. 2019 Jul 11:962280219859377. doi: 10.1177/0962280219859377. [Epub ahead of print]

PMID:
31293217
2.

Multilevel model with random effects for clustered survival data with multiple failure outcomes.

Tawiah R, Yau KKW, McLachlan GJ, Chambers SK, Ng SK.

Stat Med. 2019 Mar 15;38(6):1036-1055. doi: 10.1002/sim.8041. Epub 2018 Nov 25.

PMID:
30474216
3.

A Block EM Algorithm for Multivariate Skew Normal and Skew -Mixture Models.

Lee SX, Leemaqz KL, McLachlan GJ.

IEEE Trans Neural Netw Learn Syst. 2018 Nov;29(11):5581-5591. doi: 10.1109/TNNLS.2018.2805317. Epub 2018 Mar 9.

PMID:
29993871
4.

Whole-Volume Clustering of Time Series Data from Zebrafish Brain Calcium Images via Mixture Modeling.

Nguyen HD, Ullmann JFP, McLachlan GJ, Voleti V, Li W, Hillman EMC, Reutens DC, Janke AL.

Stat Anal Data Min. 2018 Feb;11(1):5-16. doi: 10.1002/sam.11366. Epub 2017 Dec 6.

5.

Partial identification in the statistical matching problem.

Ahfock D, Pyne S, Lee SX, McLachlan GJ.

Comput Stat Data Anal. 2016 Dec;104:79-90. doi: 10.1016/j.csda.2016.06.005.

6.

Maximum Pseudolikelihood Estimation for Model-Based Clustering of Time Series Data.

Nguyen HD, McLachlan GJ, Orban P, Bellec P, Janke AL.

Neural Comput. 2017 Apr;29(4):990-1020. doi: 10.1162/NECO_a_00938. Epub 2017 Jan 17.

PMID:
28095191
7.

Statistical Evaluation of Labeled Comparative Profiling Proteomics Experiments Using Permutation Test.

Nguyen HD, McLachlan GJ, Hill MM.

Methods Mol Biol. 2017;1549:109-117.

PMID:
27975287
8.

Clustering.

McLachlan GJ, Bean RW, Ng SK.

Methods Mol Biol. 2017;1526:345-362.

PMID:
27896751
9.

A Universal Approximation Theorem for Mixture-of-Experts Models.

Nguyen HD, Lloyd-Jones LR, McLachlan GJ.

Neural Comput. 2016 Dec;28(12):2585-2593. Epub 2016 Sep 14.

PMID:
27626962
10.

Mixture of time-dependent growth models with an application to blue swimmer crab length-frequency data.

Lloyd-Jones LR, Nguyen HD, McLachlan GJ, Sumpton W, Wang YG.

Biometrics. 2016 Dec;72(4):1255-1265. doi: 10.1111/biom.12531. Epub 2016 Apr 28.

PMID:
27123964
11.

Application of Multiple Imputation for Missing Values in Three-Way Three-Mode Multi-Environment Trial Data.

Tian T, McLachlan GJ, Dieters MJ, Basford KE.

PLoS One. 2015 Dec 21;10(12):e0144370. doi: 10.1371/journal.pone.0144370. eCollection 2015.

12.

Modeling of inter-sample variation in flow cytometric data with the joint clustering and matching procedure.

Lee SX, McLachlan GJ, Pyne S.

Cytometry A. 2016 Jan;89(1):30-43. doi: 10.1002/cyto.a.22789. Epub 2015 Oct 22.

13.

A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes.

Aghaeepour N, Chattopadhyay P, Chikina M, Dhaene T, Van Gassen S, Kursa M, Lambrecht BN, Malek M, McLachlan GJ, Qian Y, Qiu P, Saeys Y, Stanton R, Tong D, Vens C, Walkowiak S, Wang K, Finak G, Gottardo R, Mosmann T, Nolan GP, Scheuermann RH, Brinkman RR.

Cytometry A. 2016 Jan;89(1):16-21. doi: 10.1002/cyto.a.22732. Epub 2015 Oct 8.

14.

Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

Pyne S, Lee SX, Wang K, Irish J, Tamayo P, Nazaire MD, Duong T, Ng SK, Hafler D, Levy R, Nolan GP, Mesirov J, McLachlan GJ.

PLoS One. 2014 Jul 1;9(7):e100334. doi: 10.1371/journal.pone.0100334. eCollection 2014.

15.

Inference on differences between classes using cluster-specific contrasts of mixed effects.

Ng SK, McLachlan GJ, Wang K, Nagymanyoki Z, Liu S, Ng SW.

Biostatistics. 2015 Jan;16(1):98-112. doi: 10.1093/biostatistics/kxu028. Epub 2014 Jun 23.

PMID:
24963011
16.

False discovery rate control in magnetic resonance imaging studies via Markov random fields.

Nguyen HD, McLachlan GJ, Cherbuin N, Janke AL.

IEEE Trans Med Imaging. 2014 Aug;33(8):1735-48. doi: 10.1109/TMI.2014.2322369. Epub 2014 May 7.

PMID:
24816549
17.

Clustering of gene expression data via normal mixture models.

McLachlan GJ, Flack LK, Ng SK, Wang K.

Methods Mol Biol. 2013;972:103-19. doi: 10.1007/978-1-60327-337-4_7.

PMID:
23385534
18.

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects.

Wang K, Ng SK, McLachlan GJ.

BMC Bioinformatics. 2012 Nov 14;13:300. doi: 10.1186/1471-2105-13-300.

19.

On the classification of microarray gene-expression data.

Basford KE, McLachlan GJ, Rathnayake SI.

Brief Bioinform. 2013 Jul;14(4):402-10. doi: 10.1093/bib/bbs056. Epub 2012 Sep 17.

PMID:
22988257
20.

Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages.

Schroder K, Irvine KM, Taylor MS, Bokil NJ, Le Cao KA, Masterman KA, Labzin LI, Semple CA, Kapetanovic R, Fairbairn L, Akalin A, Faulkner GJ, Baillie JK, Gongora M, Daub CO, Kawaji H, McLachlan GJ, Goldman N, Grimmond SM, Carninci P, Suzuki H, Hayashizaki Y, Lenhard B, Hume DA, Sweet MJ.

Proc Natl Acad Sci U S A. 2012 Apr 17;109(16):E944-53. doi: 10.1073/pnas.1110156109. Epub 2012 Mar 26.

21.

Testing for group structure in high-dimensional data.

McLachlan GJ, Rathnayake SI.

J Biopharm Stat. 2011 Nov;21(6):1113-25. doi: 10.1080/10543406.2011.608342.

PMID:
22023680
22.

Commentary on Steinley and Brusco (2011): recommendations and cautions.

McLachlan GJ.

Psychol Methods. 2011 Mar;16(1):80-1; discussion 89-92. doi: 10.1037/a0021141.

PMID:
21381818
23.

Mixtures of common t-factor analyzers for clustering high-dimensional microarray data.

Baek J, McLachlan GJ.

Bioinformatics. 2011 May 1;27(9):1269-76. doi: 10.1093/bioinformatics/btr112. Epub 2011 Mar 3.

PMID:
21372081
24.

Mixtures of factor analyzers with common factor loadings: applications to the clustering and visualization of high-dimensional data.

Baek J, McLachlan GJ, Flack LK.

IEEE Trans Pattern Anal Mach Intell. 2010 Jul;32(7):1298-309. doi: 10.1109/TPAMI.2009.149.

PMID:
20489231
25.

Integrative mixture of experts to combine clinical factors and gene markers.

Lê Cao KA, Meugnier E, McLachlan GJ.

Bioinformatics. 2010 May 1;26(9):1192-8. doi: 10.1093/bioinformatics/btq107. Epub 2010 Mar 11.

26.

Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer.

Tang L, Yang J, Ng SK, Rodriguez N, Choi PW, Vitonis A, Wang K, McLachlan GJ, Caiazzo RJ Jr, Liu BC, Welch WR, Cramer DW, Berkowitz RS, Ng SW.

Eur J Cancer. 2010 Jan;46(1):170-9. doi: 10.1016/j.ejca.2009.10.003.

27.

A score test for assessing the cured proportion in the long-term survivor mixture model.

Zhao Y, Lee AH, Yau KK, Burke V, McLachlan GJ.

Stat Med. 2009 Nov 30;28(27):3454-66. doi: 10.1002/sim.3696.

28.

Microarray data analysis for differential expression: a tutorial.

Suárez E, Burguete A, Mclachlan GJ.

P R Health Sci J. 2009 Jun;28(2):89-104. Review.

PMID:
19530550
29.

Automated high-dimensional flow cytometric data analysis.

Pyne S, Hu X, Wang K, Rossin E, Lin TI, Maier LM, Baecher-Allan C, McLachlan GJ, Tamayo P, Hafler DA, De Jager PL, Mesirov JP.

Proc Natl Acad Sci U S A. 2009 May 26;106(21):8519-24. doi: 10.1073/pnas.0903028106. Epub 2009 May 14.

30.

Clustering.

McLachlan GJ, Bean RW, Ng SK.

Methods Mol Biol. 2008;453:423-39. doi: 10.1007/978-1-60327-429-6_22.

PMID:
18712317
31.

Bivariate mixture modeling of transferrin saturation and serum ferritin concentration in Asians, African Americans, Hispanics, and whites in the Hemochromatosis and Iron Overload Screening (HEIRS) Study.

McLaren CE, Gordeuk VR, Chen WP, Barton JC, Acton RT, Speechley M, Castro O, Adams PC, Snively BM, Harris EL, Reboussin DM, McLachlan GJ, Bean R; Hemochromatosis and Iron Overload Screening Study Research Investigators.

Transl Res. 2008 Feb;151(2):97-109. doi: 10.1016/j.trsl.2007.10.002. Epub 2007 Nov 9.

32.

Maternity length of stay modelling by gamma mixture regression with random effects.

Lee AH, Wang K, Yau KK, McLachlan GJ, Ng SK.

Biom J. 2007 Aug;49(5):750-64.

PMID:
17722201
33.

Extension of mixture-of-experts networks for binary classification of hierarchical data.

Ng SK, McLachlan GJ.

Artif Intell Med. 2007 Sep;41(1):57-67. Epub 2007 Jul 16.

PMID:
17629686
34.

Multilevel survival modelling of recurrent urinary tract infections.

Wang K, Yau KK, Lee AH, McLachlan GJ.

Comput Methods Programs Biomed. 2007 Sep;87(3):225-9. Epub 2007 Jul 9.

PMID:
17619063
35.

Application of gene shaving and mixture models to cluster microarray gene expression data.

Do KA, McLachlan GJ, Bean R, Wen S.

Cancer Inform. 2007;5:25-43. Epub 2007 Apr 2.

36.

Segmentation and intensity estimation of microarray images using a gamma-t mixture model.

Baek J, Son YS, McLachlan GJ.

Bioinformatics. 2007 Feb 15;23(4):458-65. Epub 2006 Dec 12.

PMID:
17166856
37.

Mixture models for detecting differentially expressed genes in microarrays.

Jones LB, Bean R, McLachlan GJ, Zhu JX.

Int J Neural Syst. 2006 Oct;16(5):353-62.

PMID:
17117496
38.

A score test for overdispersion in zero-inflated poisson mixed regression model.

Xiang L, Lee AH, Yau KK, McLachlan GJ.

Stat Med. 2007 Mar 30;26(7):1608-22.

PMID:
16794991
39.

A mixture model with random-effects components for clustering correlated gene-expression profiles.

Ng SK, McLachlan GJ, Wang K, Ben-Tovim Jones L, Ng SW.

Bioinformatics. 2006 Jul 15;22(14):1745-52. Epub 2006 May 3.

PMID:
16675467
40.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays.

McLachlan GJ, Bean RW, Jones LB.

Bioinformatics. 2006 Jul 1;22(13):1608-15. Epub 2006 Apr 21.

PMID:
16632494
41.

Multi-level zero-inflated poisson regression modelling of correlated count data with excess zeros.

Lee AH, Wang K, Scott JA, Yau KK, McLachlan GJ.

Stat Methods Med Res. 2006 Feb;15(1):47-61.

PMID:
16477948
42.

An incremental EM-based learning approach for on-line prediction of hospital resource utilization.

Ng SK, McLachlan GJ, Lee AH.

Artif Intell Med. 2006 Mar;36(3):257-67. Epub 2005 Oct 6.

PMID:
16213695
43.

A score test for zero-inflation in correlated count data.

Xiang L, Lee AH, Yau KK, McLachlan GJ.

Stat Med. 2006 May 30;25(10):1660-71.

PMID:
16143993
44.

Mixture modelling for cluster analysis.

McLachlan GJ, Chang SU.

Stat Methods Med Res. 2004 Oct;13(5):347-61.

PMID:
15516030
45.
46.
47.
48.

Influence of patient age and implantation technique on the probability of re-replacement of the homograft aortic valve.

Ng SK, O'Brien MF, Harrocks S, McLachlan GJ.

J Heart Valve Dis. 2002 Mar;11(2):217-23; discussion 223-5.

PMID:
12000163
49.

Selection bias in gene extraction on the basis of microarray gene-expression data.

Ambroise C, McLachlan GJ.

Proc Natl Acad Sci U S A. 2002 May 14;99(10):6562-6. Epub 2002 Apr 30.

50.

A mixture model-based approach to the clustering of microarray expression data.

McLachlan GJ, Bean RW, Peel D.

Bioinformatics. 2002 Mar;18(3):413-22.

PMID:
11934740

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