Our publications related to cancer biomarkers
DUSP4 is associated with increased resistance against anti-HER2 therapy in breast cancer. Oncotarget. 8(44):77207-77218.
.
2017. Dynamic classification using case-specific training cohorts outperforms static gene expression signatures in breast cancer.. Int J Cancer. 136(9):2091-8.
.
2015. Evaluation of microarray preprocessing algorithms based on concordance with RT-PCR in clinical samples. PLoS One. 4:e5645.
.
2009. Jetset: selecting the optimal microarray probe set to represent a gene. BMC Bioinformatics. 12:474.
.
2011. Meta-analysis of gene expression profiles related to relapse-free survival in 1,079 breast cancer patients. Breast Cancer Res Treat. 118:433-41.
.
2009. RecurrenceOnline: an online analysis tool to determine breast cancer recurrence and hormone receptor status using microarray data. Breast Cancer Res Treat. 132:1025-34.
.
2012. TP53 mutation-correlated genes predict the risk of tumor relapse and identify MPS1 as a potential therapeutic kinase in TP53-mutated breast cancers.. Mol Oncol. 8(3):508-19.
.
2014. A genome-wide approach to link genotype to clinical outcome by utilizing next generation sequencing and gene chip data of 6,697 breast cancer patients.. Genome Med. 7(1):104.
.
2015. A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer.. Breast Cancer Res Treat. 140(2):219-32.
.
2013. miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients. Breast Cancer Res Treat. 160(3):446.
.
2016.