b, Initially, we transform commonly used, curated ‘secondary’ resources into configurable, task-specific knowledge graphs in various output formats. Incrementally, these secondary adapters will be replaced by primary resource adapters (Supplementary Fig. 1). Colored panels in a,b indicate parts of the BioCypher ecosystem.

c, Agreeing on a common representational framework allows harmonization of task-specific data sources to answer complex queries across biomedical domains. For instance, starting at mass spectrometry measurements of a patient’s tumor (left), one could go through clinical annotations to genetic dependencies from the Dependency Map project to identify potential drug targets or through pathway or process annotations in Reactome and IntAct, identify relevant ligand–receptor pairs using OmniPath, and use CROssBAR to perform drug discovery or repurposing for these receptors. Panels correspond to resources; although we work on most of the displayed resources, the figure is used for illustrative purposes and does not depict an existing pipeline.

安装

biocypher使用了poetry管理依赖  poetry需要运行在一个虚拟环境中 biocypher依赖python3.9
sudo apt install python3.9-venv
mkdir biocypher && cd "$_"
python3.9 -m venv .biocypher
source .biocypher/bin/activate
pip install -U pip setuptools
pip install poetry