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2011

Journal Article

Classification of high-dimensional microarray data with a two-step procedure via a Wilcoxon criterion and multilayer perceptron

Nikulin, Vladimir, Huang, Tian-Hsiang and McLachlan, Geoffrey J. (2011). Classification of high-dimensional microarray data with a two-step procedure via a Wilcoxon criterion and multilayer perceptron. International Journal of Computational Intelligence and Applications, 10 (1), 1-14. doi: 10.1142/S1469026811002969

Classification of high-dimensional microarray data with a two-step procedure via a Wilcoxon criterion and multilayer perceptron

2011

Journal Article

Commentary on Steinley and Brusco (2011): Recommendations and cautions

McLachlan, Geoffrey J. (2011). Commentary on Steinley and Brusco (2011): Recommendations and cautions. Psychological Methods, 16 (1), 80-81. doi: 10.1037/a0021141

Commentary on Steinley and Brusco (2011): Recommendations and cautions

2011

Journal Article

Assessing the adequacy of Weibull survival models: a simulated envelope approach

Zhao, Yun, Lee, Andy H., Yau, Kelvin K.W. and McLachlan, Geoffrey J. (2011). Assessing the adequacy of Weibull survival models: a simulated envelope approach. Journal of Applied Statistics, 38 (10), 2089-2097. doi: 10.1080/02664763.2010.545115

Assessing the adequacy of Weibull survival models: a simulated envelope approach

2011

Book Chapter

Mixtures of factor analyzers for the analysis of high-dimensional data

McLachlan, Geoffrey J., Baek, Jangsun and Rathnayake, Suren I. (2011). Mixtures of factor analyzers for the analysis of high-dimensional data. Mixture estimation and applications. (pp. 189-212) edited by Kerrie L. Mengersen, Christian P. Robert and D. Michael Titterington. Chichester, United Kingdom: John Wiley and Sons. doi: 10.1002/9781119995678.ch9

Mixtures of factor analyzers for the analysis of high-dimensional data

2011

Journal Article

Testing for Group Structure in High-Dimensional Data

McLachlan, G. J. and Rathnayake, S. I. (2011). Testing for Group Structure in High-Dimensional Data. Journal of Biopharmaceutical Statistics, 21 (6), 1113-1125. doi: 10.1080/10543406.2011.608342

Testing for Group Structure in High-Dimensional Data

2010

Journal Article

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

Baek, Jangsun, McLachlan, Geoffrey J. and Flack, Lloyd K. (2010). Mixtures of factor analyzers with common factor loadings: Applications to the clustering and visualization of high-dimensional data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (7) 5184847, 1298-1309. doi: 10.1109/TPAMI.2009.149

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

2010

Journal Article

Integrative mixture of experts to combine clinical factors and gene markers

Le Cao, Kim-Anh, Meugnier, Emmanuelle and McLachlan, Geoffrey J. (2010). Integrative mixture of experts to combine clinical factors and gene markers. Bioinformatics, 26 (9) btq107, 1192-1198. doi: 10.1093/bioinformatics/btq107

Integrative mixture of experts to combine clinical factors and gene markers

2010

Conference Publication

Clustering of High-Dimensional Data via Finite Mixture Models

McLachlan, Geoff J. and Baek, Jangsun (2010). Clustering of High-Dimensional Data via Finite Mixture Models. 32nd Annual Conference of the German-Classification-Society, Hamburg Germany, Jul 16-18, 2008. BERLIN: SPRINGER-VERLAG BERLIN. doi: 10.1007/978-3-642-01044-6_3

Clustering of High-Dimensional Data via Finite Mixture Models

2010

Conference Publication

Automated high-dimensional flow cytometric data analysis

Pyne, Saumyadipta, Hu, Xinli, Wang, Kui, Rossin, Elizabeth, Lin, Tsung-I, Maier, Lisa, Baecher-Allan, Clare, McLachlan, Geoffrey, Tamayo, Pablo, Hafler, David, De Jager, Philip and Mesirov, Jill (2010). Automated high-dimensional flow cytometric data analysis. 14th Annual International Conference on Research in Computational Molecular Biology, Lisbon, Portugal, 25-28 April 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-12683-3_41

Automated high-dimensional flow cytometric data analysis

2010

Conference Publication

On the gradient-based algorithm for matrix factorization applied to dimensionality reduction

Nikulin, Vladimir and McLachlan, Geoffrey J. (2010). On the gradient-based algorithm for matrix factorization applied to dimensionality reduction. BIOINFORMATICS 2010: 1st International Conference on Bioinformatics, Valencia, Spain, 20-23 January 2010. Portugal: Institute for Systems and Technologies of Information, Control and Communication.

On the gradient-based algorithm for matrix factorization applied to dimensionality reduction

2010

Conference Publication

On relations between genes and metagenes obtained via gradient-based matrix factorization

Huang, Tian-Hsiang, Nikulin, Vladimir and McLachlan, Geoffrey J. (2010). On relations between genes and metagenes obtained via gradient-based matrix factorization. 2010 IEEE/ICME International Conference on Complex Medical Engineering, Gold Coast, Australia, 13-15 July 2010. Piscataway, United States: IEEE Computer Society. doi: 10.1109/ICCME.2010.5558880

On relations between genes and metagenes obtained via gradient-based matrix factorization

2010

Journal Article

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

Tang, Liangdan, Yang, Junzheng, Ng, Shu-Kay, Rodriguez, Noah, Choi, Pui-Wah, Vitonis, Allison, Wang, Kui, McLachlan, Geoffrey J., Caiazzo, Robert J., Liu, Brian C.-S., Welch, Brian C.-S., Cramer, Daniel W., Berkowitz, Ross S. and Ng, Shu-Wing (2010). Autoantibody profiling to identify biomarkers of key pathogenic pathways in mucinous ovarian cancer. European Journal of Cancer, 46 (1), 170-179. doi: 10.1016/j.ejca.2009.10.003

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

2010

Conference Publication

RSCTC 2010 Discovery Challenge: Mining DNA microarray data for medical diagnosis and treatment

Wojnarski, Marcin, Janusz, Andrzej, Nyugen, Hung Son, Bazan, Jan, Luo, ChuanJiang, Chen, Ze, Hu, Feng, Wang, Guoyin, Guan, Lihe, Luo, Huan, Gao, Juan, Shen, Yuanxia, Nikulin, Vladimir, Huang, Tian-Hsiang, McLachlan, Geoffrey J., Bosnjak, Matko and Gamberger, Dragan (2010). RSCTC 2010 Discovery Challenge: Mining DNA microarray data for medical diagnosis and treatment. 7th International Conference on Rough Sets and Current Trends in Computing (RSCTC 2010), Warsaw, Poland, 28-30 June 2010. Heidelberg, Germany: Springer. doi: 10.1007/978-3-642-13529-3_3

RSCTC 2010 Discovery Challenge: Mining DNA microarray data for medical diagnosis and treatment

2010

Book Chapter

Expert networks with mixed continuous and categorical feature variables: A location modeling approach.

Ng, Shu-Kay and McLachlan, Geoffrey J. (2010). Expert networks with mixed continuous and categorical feature variables: A location modeling approach.. Machine learning research progress. (pp. 355-368) edited by Hannah Peters and Mia Vogel. New York, U.S.A.: Nova Science.

Expert networks with mixed continuous and categorical feature variables: A location modeling approach.

2010

Conference Publication

Penalized principal component analysis of microarray data

Nikulin, Vladimir and McLachlan, Geoffrey J. (2010). Penalized principal component analysis of microarray data. 6th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2009, Genoa, Italy, 15-17 October, 2009. Germany: Springer. doi: 10.1007/978-3-642-14571-1_7

Penalized principal component analysis of microarray data

2010

Book Chapter

Clustering of high-dimensional data via finite mixture models

McLachlan, Geoff J. and Baek, Jangsun (2010). Clustering of high-dimensional data via finite mixture models. Advances in Data Analysis, Business Intelligence: Proceedings of the 32nd Annual Conference of the Gesellschaft für Klassifikation e.V., Joint Conference with the British Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC Helmut-Schmidt-University, Hamburg, July 16–18, 2008. (pp. 33-44) edited by Andreas Fink, Berthold Lausen, Wilfried Seidel and Alfred Ultsch. Heidelberg, Germany: Springer-Verlag. doi: 10.1007/978-3-642-01044-6

Clustering of high-dimensional data via finite mixture models

2010

Conference Publication

Use of mixture models in multiple hypothesis testing with applications in bioinformatics

McLachlan, Geoffrey J. and Wockner, Leesa (2010). Use of mixture models in multiple hypothesis testing with applications in bioinformatics. Classification as a Tool for Research (GfKl 2009), Dresden, Germany, 13-18 March 2009. doi: 10.1007/978-3-642-10745-0-18

Use of mixture models in multiple hypothesis testing with applications in bioinformatics

2010

Conference Publication

A comparative study of two matrix factorization methods applied to the classification of gene expression rate

Nikulin, Vladimir, Huang, Tian-Hsiang and McLachlan, Geoffrey J. (2010). A comparative study of two matrix factorization methods applied to the classification of gene expression rate. IEEE International Conference on Bioinformatics & Biomedicine, Hong Kong, 18-21 December 2010. Los Alamitos, CA, U.S.A.: IEEE Computer Society. doi: 10.1109/bibm.2010.5706640

A comparative study of two matrix factorization methods applied to the classification of gene expression rate

2010

Conference Publication

Identifying fibre bundles with regularized k-means clustering applied to grid-based data

Nikulin, Vladimir and McLachlan, Geoffrey J. (2010). Identifying fibre bundles with regularized k-means clustering applied to grid-based data. 2010 International Joint Conference on Neural Networks (IJCNN 2010), Barcelona, Spain, 18-23 July 2010. United States: IEEE Computer Society. doi: 10.1109/IJCNN.2010.5596562

Identifying fibre bundles with regularized k-means clustering applied to grid-based data

2010

Book Chapter

Clustering of high-dimensional and correlated data

McLachlan, Geoffrey J., Ng, Shu-Kay and Wang, K. (2010). Clustering of high-dimensional and correlated data. Data Analysis and Classification: Proceedings of the 6th Conference of the Classification and Data Analysis Group of the SocietàItaliana di Statistica, Macerata, Italy 12-14 September, 2007. (pp. 3-11) edited by Francesco Palumbo, Carlo Natale Lauro and Michael J. Greenacre. Berlin; Heidelberg, Germany: Springer - Verlag. doi: 10.1007/978-3-642-03739-9_1

Clustering of high-dimensional and correlated data