Interpretable machine learning for cancer dependencies
We build machine learning tools for enhanced interpretability, suitable for the discovery and assessment of cancer vulnerabilities — designed for biologically interpretable prediction of viability readouts and their association with molecular context.
hover a node, or a module label



