Invited.- Plasticity in cancer cell populations: biology, mathematics and philosophy of cancer.- Statistical and Machine Learning Methods for Cancer Research.- CHIMERA: Combining Mechanistic Models and Machine Learning for Personalized Chemotherapy and Surgery Sequencing in Breast Cancer.- Fine-Tuning Deep Learning Architectures for Early Detection of Oral Cancer.- Discriminative Localized Sparse Representations for Breast Cancer Screening.- Activation vs. Organization: Prognostic Implications of T and B cell Features of the PDAC Microenvironment.- On the use of neural networks with censored time-to-event data.- Mathematical Modeling for Cancer Research.- tugHall: a tool to reproduce Darwinian evolution of cancer cells for simulation-based personalized medicine.- General Cancer Computational Biology.- The potential of single cell RNA-sequencing data for the prediction of gastric cancer serum biomarkers.- Poster.- Theoretical Foundation of the Performance of Phylogeny-Based Somatic Variant Detection.- Detecting subclones from spatially resolved RNA-seq data.- Novel driver synonymous mutations in the coding regions of GCB lymphoma patients improve the transcription levels of BCL2.