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2013

Journal Article

How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification: written contribution to the discussion on the paper by Hennig and Liao

McLachlan, G. J. (2013). How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification: written contribution to the discussion on the paper by Hennig and Liao. Applied Statistics-Journal of the Royal Statistical Society Series C, 62 (3), 309-369. doi: 10.1111/j.1467-9876.2012.01066.x

How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification: written contribution to the discussion on the paper by Hennig and Liao

2013

Journal Article

Critical assessment of automated flow cytometry analysis techniques

Aghaeepour, Nima, Finak, Greg, Hoos, Holger, Mosmann, Tim R., Brinkman, Ryan, Gottardo, Raphael, Scheuermann, Richard H., The FlowCAP Consortium, McLachlan, Geoffrey J., Wang, Kui and The DREAM Consortium (2013). Critical assessment of automated flow cytometry analysis techniques. Nature Methods, 10 (3), 228-238. doi: 10.1038/nmeth.2365

Critical assessment of automated flow cytometry analysis techniques

2013

Conference Publication

On finite mixtures of skew distributions

McLachlan, Geoffrey J. and Leemaqz, Sharon X. (2013). On finite mixtures of skew distributions. 28th International Workshop on Statistical Modelling, Palermo, Italy, 8-12 July 2013. Amsterdam: Statistical Modelling Society.

On finite mixtures of skew distributions

2013

Conference Publication

A common factor-analytic model for classification

Sun, Mingzhu and McLachlan, Geoffrey J (2013). A common factor-analytic model for classification. IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, Shanghai China, 18 - 21 December 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/BIBM.2013.6732722

A common factor-analytic model for classification

2013

Book Chapter

Clustering of gene expression data via normal mixture models

McLachlan, G. J., Flack, L. K., Ng, S. K. and Wang, K. (2013). Clustering of gene expression data via normal mixture models. Statistical methods for microarray data analysis: methods and protocols. (pp. 103-119) edited by Andrei Y. Yakovlev, Lev Klebanov and Daniel Gaile. New York, NY, United States: Humana Press. doi: 10.1007/978-1-60327-337-4_7

Clustering of gene expression data via normal mixture models

2013

Conference Publication

Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes

Ng, Shu-Kay and McLachlan, Geoffrey J. (2013). Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes. IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2013, Shanghai, China, 18 - 21 December 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/BIBM.2013.6732501

Using cluster analysis to improve gene selection in the formation of discriminant rules for the prediction of disease outcomes

2013

Journal Article

On the classification of microarray gene-expression data

Basford, Kaye E., McLachlan, Geoffrey J. and Rathnayake, Suren I. (2013). On the classification of microarray gene-expression data. Briefings in Bioinformatics, 14 (4) bbs056, 402-410. doi: 10.1093/bib/bbs056

On the classification of microarray gene-expression data

2013

Conference Publication

Evaluating methods of estimating missing values for three-way three-mode multi-environment trial data

Tian, Ting, McLachlan, Geoff, Dieters, Mark and Basford, Kaye (2013). Evaluating methods of estimating missing values for three-way three-mode multi-environment trial data. Biometrics by the Canals: The International Biometric Society Australasian Region Conference 2013, Mandura, WA, Australia, 1-5 December, 2013.

Evaluating methods of estimating missing values for three-way three-mode multi-environment trial data

2013

Conference Publication

Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk

Lee, Sharon X. and McLachlan, Geoffrey J. (2013). Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk. International Congress on Modelling and Simulation, Adelaide, SA, Australia, 1/12/2013/6/12/2013. Melbourne, Australia: Modelling and Simulation Society of Australia and New Zealand.

Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk

2013

Conference Publication

Preface

Kim, Sunghoon, Li, Guo-Zheng, Ressom, Habtom, Hughes, Michael, Liu, Baoyan, McLachlan, Geoff, Liebman, Michael, Sun, Hongye and Hu, Xiaohua (2013). Preface. 2013 IEEE International Conference on Bioinformatics and Biomedicine, Shanghai, China, 18-21 December 2013. Minerals, Metals and Materials Society. doi: 10.1109/BIBM.2013.6732445

Preface

2013

Conference Publication

Spatial false discovery rate control for magnetic resonance imaging studies

Nguyen, Hien D., McLachlan, Geoffrey J., Janke, Andrew L., Cherbuin, Nicolas, Sachdev, Perminder and Anstey, Kaarin J. (2013). Spatial false discovery rate control for magnetic resonance imaging studies. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013, Hobart, TAS, 26 - 28 November 2013. Piscataway, NJ United States: I E E E. doi: 10.1109/DICTA.2013.6691531

Spatial false discovery rate control for magnetic resonance imaging studies

2012

Journal Article

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

Wang, Kui, Ng, Shu Kay and McLachlan, Geoffrey J. (2012). Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects. Bmc Bioinformatics, 13 (1) 300, 300.1-300.14. doi: 10.1186/1471-2105-13-300

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

2012

Journal Article

Discriminant analysis

McLachlan, Geoffrey J. (2012). Discriminant analysis. Wiley Interdisciplinary Reviews: Computational Statistics., 4 (5), 421-431. doi: 10.1002/wics.1219

Discriminant analysis

2012

Journal Article

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

Schroder, Kate, Irvine, Katharine M., Taylor, Martin S., Bokil, Nilesh J., Le Cao, Kim-Anh, Masterman, Kelly-Anne, Labzin, Larisa I., Semple, Colin A., Kapetanovic, Ronan, Fairbairn, Lynsey, Akalin, Altuna, Faulkner, Geoffrey J., Baillie, John Kenneth, Gongora, Milena, Daub, Carsten O., Kawaji, Hideya, McLachlan, Geoffrey J., Goldman, Nick, Grimmond, Sean M., Carninci, Piero, Suzuki, Harukazu, Hayashizaki, Yoshihide, Lenhard, Boris, Hume, David A. and Sweet, Matthew J. (2012). Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages. Proceedings of the National Academy of Sciences of the USA, 109 (16), E944-E953. doi: 10.1073/pnas.1110156109

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

2012

Journal Article

Top-10 data mining case studies

Melli, Gabor, Wu, Xindong, Beinat, Paul, Bonchi, Francesco, Cao, Longbing, Duan, Rong, Faloutsos, Christos, Ghani, Rayid, Kitts, Brendan, Goethals, Bart, McLachlan, Geoff, Pei, Jian, Srivastava, Ashok and Zaiane, Osmar (2012). Top-10 data mining case studies. International Journal of Information Technology and Decision Making, 11 (2), 389-400. doi: 10.1142/S021962201240007X

Top-10 data mining case studies

2012

Book Chapter

An enduring interest in classification: supervised and unsupervised

McLachlan, G. J. (2012). An enduring interest in classification: supervised and unsupervised. Journeys to data mining: experiences from 15 renowned researchers. (pp. 147-171) edited by Mohamed Medhat Gaber. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-28047-4_12

An enduring interest in classification: supervised and unsupervised

2012

Book Chapter

The EM algorithm

Ng, Shu Kay, Krishnan, Thriyambakam and McLachlan, Geoffrey J. (2012). The EM algorithm. Handbook of Computational Statistics: Concepts and Methods. (pp. 139-172) edited by James E. Gentle, Wolfgang Karl Hardle and Yuichi Mori. Berlin & New York: Springer. doi: 10.1007/978-3-642-21551-3__6

The EM algorithm

2011

Book Chapter

The EM Algorithm

Ng, Shu Kay, Krishnan, Thriyambakam and McLachlan, Geoffrey J. (2011). The EM Algorithm. Handbook of Computational Statistics. (pp. 139-172) Berlin, Germany: Springer. doi: 10.1007/978-3-642-21551-3_6

The EM Algorithm

2011

Journal Article

A very fast algorithm for matrix factorization

Nikulin, V, Huang, TH, Ng, SK, Rathnayake, SI and McLachlan, GJ (2011). A very fast algorithm for matrix factorization. Statistics and Probability Letters, 81 (7), 773-782. doi: 10.1016/j.spl.2011.02.001

A very fast algorithm for matrix factorization

2011

Journal Article

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

Baek, Jangsun and McLachlan, Geoffrey J. (2011). Mixtures of common t-factor analyzers for clustering high-dimensional microarray data. Bioinformatics, 27 (9) btr112, 1269-1276. doi: 10.1093/bioinformatics/btr112

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