cancer

Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing

Code for the Nature Scientific Reports paper "Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks." A sliding window framework for classification of high resolution whole-slide images, often microscopy or histopathology images.

A community-maintained repository of cancer clinical knowledge bases and databases focused on cancer variants.

Personalized Genomics and Proteomics. Main diet: Ensembl, side dishes: SNPs

Personal Cancer Genome Reporter (PCGR)

Fast and accurate gene fusion detection from RNA-Seq data

A list of web-based interactive biological data visualizations.

This project is all about a Machine Learning based Medical Test web app which makes predictions about various diseases using the concept of machine learning.

Opensource Python project for cancer radiation treatment planning [AAPM'23]

Cancer Imaging Phenomics Toolkit (CaPTk) is a software platform to perform image analysis and predictive modeling tasks. Documentation: https://cbica.github.io/CaPTk

Health Check ✔ is a Machine Learning Web Application made using Flask that can predict mainly three diseases i.e. Diabetes, Heart Disease, and Cancer.

Training and evaluating a variational autoencoder for pan-cancer gene expression data

P-NET, Biologically informed deep neural network for prostate cancer classification and discovery

OnCo: total information dominance on cancer. A public, cited knowledge graph of oncology with a website, JSON API, MCP server and CLI: one page per cancer, treatment, target, trial, institution, person and idea, plain English first, solution and mechanism first.

Detect and visualize target mutations by scanning FastQ files directly

Notebooks to follow along with "Deep Learning for Biology" Chapters 2 to 6.

BioDynaMo is a high-performance and modular, agent-based simulation platform.

Notebooks for working with The Cancer Imaging Archive datasets. Have you written one? Submit a PR!

Detect germline or somatic variants from normal or tumour/normal whole-genome or targeted sequencing