Bladder Cancer Microarray Analysis and Biomarker Discovery Using Machine Learning

This publication has 30 references indexed in Scilit:

• Global cancer statistics, 2012
  CA: A Cancer Journal for Clinicians, 2015
• Big data mining yields novel insights on cancer
  Nature Genetics, 2015
• limma powers differential expression analyses for RNA-sequencing and microarray studies
  Nucleic Acids Research, 2015
• A Comparison of Methods for RNA-Seq Differential Expression Analysis and a New Empirical Bayes Approach
  Biosensors, 2013
• Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool
  BMC Bioinformatics, 2013
• Epidemiology and Risk Factors of Urothelial Bladder Cancer
  European Urology, 2013
• Benjamini–Hochberg Method
  2013
• Elastic-net regularization in learning theory
  Journal of Complexity, 2009
• The effect of GeneChip gene definitions on the microarray study of cancers
  BioEssays, 2006
• Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
  Proceedings of the National Academy of Sciences, 2005