Browse by all authors Browse By Author ID - Jones, Liat

Browse Results (9 results found)

Subscribe to the RSS feed for this result setSubscribe to the RSS feed for this result set


  Abstract Views File Downloads Thomson Reuters Web of Science Citation Count Scopus Citation Count Altmetric Score
Ng, SK, McLachlan, GJ, Wang, K, Jones, LBT and Ng, SW (2006) A Mixture model with random-effects components for clustering correlated gene-expression profiles. Bioinformatics, 22 14: 1745-1752. doi:10.1093/bioinformatics/btl165 1000   67 Cited 73 times in Scopus73 0
Jones, LBT, Bean, R, McLachlan, G and Zhu, J (2005) Application of mixture models to detect differentially expressed genes. Intelligent Data Engineering And Automated Learning Ideal 2005, Proceedings, 3578 -: 422-431. 65   1 Cited 1 times in Scopus1
McLachlan, GJ, Bean, RW and Jones, LBT (2006) A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays. Bioinformatics, 22 13: 1608-1615. doi:10.1093/bioinformatics/btl148 66   75 Cited 81 times in Scopus81 0
McLachlan, G. J., Bean, R. W. and Jones, L. B. T. (2007) Extension of the Mixture of Factor Analyzers Model to Incorporate the Multivariate t-Distribution. Computational Statistics & Data Analysis, 51 11: 5327-5338. doi:10.1016/j.csda.2006.09.015 80   46 Cited 48 times in Scopus48 0
Jones, L., Ng, A.S. K., Monico, K. A. and McLachlan, G. J. (2004). Linking gene-expression experiments with survival-time data. In: A. Biggeri and et al, Proceedings of the 19th International Workship on Statistical Modelling. 19th International Workshop on Statistical Modelling, Florence, (71-75). 4-8 July 2004. 59  
Jones, L. B. T., Bean, R., McLachlan, G. J. and Zhu, J. X. (2006) Mixture models for detecting differentially expressed genes in microarrays. International Journal of Neural Systems, 16 5: 353-362. doi:10.1142/S0129065706000755 44   3 Cited 3 times in Scopus3 0
Zhu, J. X., McLachlan, G. J., Jones, L. B. T. and Wood, I. A. (2008) On selection biases with prediction rules formed from gene expression data. Journal of Statistical Planning and Inference, 138 2: 374-386. doi:10.1016/j.jspi.2007.06.003 58   9 Cited 8 times in Scopus8 0
Jones, L., Ng, S., Ambroise, C, Monico, K. A., Khan, N. and McLachlan, G. J. (2005). Use of microarray data via model-based classification in the study and prediction of survival from lung cancer. In Jennifer S. Shoemaker and Simon M. Lin (Ed.), Methods of microarray data analysis IV (pp. 163-173) New York, USA: Springer. doi:10.1007/0-387-23077-7_13 50   1 0
McLachlan, G. J., Bean, R. W., Jones, L. and Zhu, J. X. (2005) Using mixture models to detect differentially expressed genes. Australian Journal Of Experimental Agriculture, 45 7-8: 859-866. doi:10.1071/EA05051 49   13 Cited 14 times in Scopus14 0