A mixture model-based approach to the clustering of microarray expression data von McLachlan, G. J., Bean, R. W., Peel, D.

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A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays von McLachlan, G.J., Bean, R.W., Jones, L. Ben-Tovim

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A benchmark for evaluation of algorithms for identification of cellular correlates of clinical outcomes von Aghaeepour, Nima, Chattopadhyay, Pratip, Chikina, Maria, Dhaene, Tom, Van Gassen, Sofie, Kursa, Miron, Lambrecht, Bart N., Malek, Mehrnoush, McLachlan, G. J., Qian, Yu, Qiu, Peng, Saeys, Yvan, Stanton, Rick, Tong, Dong, Vens, Celine, Walkowiak, Sławomir, Wang, Kui, Finak, Greg, Gottardo, Raphael, Mosmann, Tim, Nolan, Garry P., Scheuermann, Richard H., Brinkman, Ryan R.

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A Mixture model with random-effects components for clustering correlated gene-expression profiles von Ng, S. K., McLachlan, G. J., Wang, K., Ben-Tovim Jones, L., Ng, S.-W.

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Modelling high-dimensional data by mixtures of factor analyzers von McLachlan, G.J., Peel, D., Bean, R.W.

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Selection Bias in Gene Extraction on the Basis of Microarray Gene-Expression Data von Ambroise, Christophe, McLachlan, Geoffrey J.

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Mixture models for clustering multilevel growth trajectories von Ng, S.K., McLachlan, G.J.

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Clustering von McLachlan, G. J., Bean, R. W., Ng, S. K.

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On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples von McLachlan, G.J., Khan, N.

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Distribution of transferrin saturation in an Australian population: Relevance to the early diagnosis of hemochromatosis von McLaren, Christine E., McLachlan, Geoffrey J., Halliday, June W., Webb, Sonja I., Leggett, Barbara A., Jazwinska, Elizabeth C., Crawford, Darrell H.G., Gordeuk, Victor R., McLaren, Gordon D., Powell, Lawrie W.

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An EM-based semi-parametric mixture model approach to the regression analysis of competing-risks data von Ng, S. K., McLachlan, G. J.

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Extension of the mixture of factor analyzers model to incorporate the multivariate t-distribution von McLachlan, G.J., Bean, R.W., Ben-Tovim Jones, L.

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Mixture modelling for cluster analysis von McLachlan, G J, Chang, S U

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Modelling the distribution of ischaemic stroke-specific survival time using an EM-based mixture approach with random effects adjustment von Ng, S. K., McLachlan, G. J., Yau, Kelvin K. W., Lee, Andy H.

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On Bootstrapping the Likelihood Ratio Test Statistic for the Number of Components in a Normal Mixture von McLachlan, G. J.

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Aortic valve infection. Risk factors for death and recurrent endocarditis after aortic valve replacement von McGiffin, DC, Galbraith, AJ, McLachlan, GJ, Stower, RE, Wong, ML, Stafford, EG, Gardner, MA, Pohlner, PG, O'Brien, MF

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Cluster analysis and related techniques in medical research von McLachlan, GJ

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Testing for Group Structure in High-Dimensional Data von McLachlan, G. J., Rathnayake, Suren I.

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An analysis of valve re-replacement after aortic valve replacement with biologic devices von McGiffin, David C., Galbraith, Andrew J., O'Brien, Mark F., McLachlan, Geoffrey J., Naftel, David C., Adams, Peter, Reddy, Seenu, Early, Lesley

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Application of Gene Shaving and Mixture Models to Cluster Microarray Gene Expression Data von Do, K-A., McLachlan, G.J., Bean, R., Wen, S.

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