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Wessels LF, van Vliet MH, Horlings HM, van den vijver MJ, Reinders MJ. Integration of Clinical and Gene Expression Data Has a Synergetic Effect on Predicting Breast Cancer Outcome. PLOS ONE. 2012;7(7).
van Vliet MH, Wessels LF, Reinders MJ. Knowledge driven decomposition of tumor expression profiles. BMC Bioinformatics (Asia Pacific Bioinformatics Conference). 2009;10(Suppl 1):S20.
Kooter R. A comparison of supervised gene set searching algorithms for outcome prediction of breast cancer.; 2009.
van Vliet MH, Wessels LF, Reinders MJ. A novel approach to subtype tumors by association with single gene perturbation fingerprints. In: Fourteenth annual conference of the Advanced School for Computing and Imaging.; 2008. p. 376-83.
Reyal F, van Vliet MH, Armstrong N, Horlings HM, de Visser K, Kok M, et al. A comprehensive analysis of prognostic signatures reveals the high predictive capacity of Proliferation, Immune response and RNA splicing modules in breast cancer. Breast Cancer Res. 2008;10:R93.
van Vliet MH, Reyal F, Horlings HM, van de Vijver MJ, Reinders MJ, Wessels LF. Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability. BMC Genomics. 2008;9:375.
Foijer F, Simonis M, van Vliet MH, Wessels LF, Kerkhoven RM, Sorger PK, et al. Oncogenic pathways impinging on the G(2)-restriction point. Oncogene. 2007;Published online.
Liu X, Holstege H, van der Gulden H, Treur-Mulder M, Zevenhoven J, Velds A, et al. Somatic loss of BRCA1 and p53 in mice induces mammary tumors with features of human BRCA1-mutated basal-like breast cancer. Proc Natl Acad Sci U S A. 2007.
van Vliet MH, Klijn CN, Wessels LF, Reinders MJ. Module-Based Outcome Prediction Using Breast Cancer Compendia. PLoS ONE. 2007;2:e1047.
Taskesen E. Novel approaches for cross-species subtype identification. Delft University of Technology; 2007.