MetaOmGraph: a workbench for interactive exploratory data analysis of large expression datasets

Targeted and non-targeted anticancer drugs and drug regimens

Open-source software pipeline for cancer classification from high-throughput data using machine learning.

A Machine Learning Classifier for Lung & Colon Cancer Histopathological Images.

Autoencoders - a deep neural network was used for feature extraction followed by clustering of the "Cancer" dataset using k-means technique

Improving Information Extraction from Pathology Reports using Named Entity Recognition

We used different machine learning approaches to build models for detecting and visualizing important prognostic indicators of breast cancer survival rate. This repository contains R source codes for 5 steps which are, model evaluation, Random Forest further modelling, variable importance, decision tree and survival analysis. These can be a pipe…

The first GANs-based omics-to-omics translation framework

Bioconductor R-package: Curated Prostate Cancer Data

Predicting chemosensitivity using gene expression

💹 The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center …

A Platypus-based variant calling pipeline for cancer data

Breast Cancer Detection

Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems

A Python client for the cbioPortal Cancer API.

An example of predicting breast cancer using existing data to learn with decision trees (scikit-learn/python)

A comprehensive comparison of decision tree and random forest for cancer classification.

Helping cancer patients find a second opinion anywhere in the US within seconds.

Feature selection comparison in breath cancer dataset

Examples on processing and working with TCGA mutation and RNA-Seq data