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netinfpriors

R code accompanying Olsen et al., Frontiers In Genetics, 2014

nnunet_segmentation_model_benchmark

node-react-boilerplate

npm1-aml

orcestra

ORCESTRA is a new web application that enables users to search, request and manage pharmacogenomic datasets (PSets).

orcestra2cbio

Script to download ICB data from ORCESTRA and creates files to upload to cBioPortal

ovcsubtypes

pdac-subtyping-drugresponse

pdacsurv

Meta-analysis of prognostic models for PDAC

pdatk

pdo_bme_ekgel

pgx_guidelines

pgxcwl

pgxvision

PGxVision is short for PharmacoGenomic VISualisation and InterpretatiON. This R package is a Shiny dashboard that lets users visualize RNA-based cancer biomarkers for drug response and prognosis.

pharmacodb

Search across publicly available datasets to find instances where a drug or cell line of interest has been profiled.

pharmacodb-js

Search across publicly available datasets to find instances where a drug or cell line of interest has been profiled.

pharmacodb-scripts

pharmacodi

The PharmacoDI Python package contains all the functions needed to make the PharmacoDB database tables from a collection of .csv for each PSet.

pharmacodi_snakemake_pipeline

A Snakemake pipeline to automate the scripts for creating all PharmacoDB database tables and allow easy deployment on a range of platforms.

pharmacogx

R package to analyze large-scale pharmacogenomic datasets.

pharmacogxml

Workshop for Machine Learning in pharmacogenomics

predictio

predictio-webapp

An web application that allows users to explore gene signatures in immunotherapy studies of ICB-treated patients, and to obtain gene signature predictions using molecular data of their own studies of ICB-treated patients.

predictionet

This package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases.The main function is able to generate networks using bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer network with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen

predictior

prmt5i_gbm

ptl-oar-segmentation

Boilerplate for PyTorch Lightning based medical-image segmentation pipeline for to enable automated segmentation of organs-at-risk (in head and neck cancer) by using Simple Open-Source 3D CNNS

pykulgap

pymrmre

qanpcrt

Quality Assurance of Nasopharyngeal Cancer Radiation Therapy Targets (CTV's) using a novel web-based quality assurance application