Personal Cancer Genome Reporter (PCGR)

EcoTyper is a machine learning framework for large-scale identification of cell states and cellular ecosystems from gene expression data.

Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-parametric MRI based Convolutional Neural Network Model

Tool to estimate purity of tumor samples exploiting DNA Methylation data

A clinical genomics-guided prioritizing strategy enables accurately selecting proper cancer cell lines for biomedical research

Comparison of Tumor and Normal Cells Protein-Protein Interaction Network Parameters

Weighted In Silico Pathology: a novel approach to assess intra-tumoral heterogeneity

🦀 R interface to tumopp

Tumor Evolution Paths Project

This plot is useful for the comparison of mutational load across the cancer types, with input data in 2 coulmns i.e cancer types and mutatonal load for each samples in specificed cancer type.