Vol 3, No 3 (June 20, 2014): Translational Cancer Research (Statistical and Bioinformatics Applications in Biomedical Omics Research)

Statistical and bioinformatics applications in biomedical omics research

Sparse principal component analysis in cancer research

Artificial neural networks in the cancer genomics frontier

Integrative clustering methods for high-dimensional molecular data

A recursively partitioned mixture model for clustering time-course gene expression data

Identification of cancer mechanisms through computational systems modeling

An improved understanding of cancer genomics through massively parallel sequencing

Statistical strategies for microRNAseq batch effect reduction

Computational methods and opportunities for phosphorylation network medicine

Biomarker adaptive designs in clinical trials

Harnessing the immune system to cure cancer