depmap

What you need to process the Quarterly DepMap-Omics releases from Terra

Cancer Dependency Map package

CanDI - A global cancer data integrator

Falsification-first research on cancer genetic vulnerabilities that replicate across independent CRISPR screens.

An integrative resource for deubiquitinating enzymes (DUBs) served at https://labsyspharm.github.io/dubportal

Package to predict dependencies between cell lines and genes using Network Representation Learning (NRL) based Link Prediction

multi-omic CTS extension and dependency-prediction ML model

DeepVul: A Multi-Task Transformer Model for Joint Prediction of Gene Essentiality and Drug Response

Multi-omics kinase target prioritization pipeline for triple-negative breast cancer (TNBC) — CTS scoring across 90 real RTK/NRTK kinases.

Multi-omic computational pipeline for prioritizing combination-therapy hypotheses in triple-negative breast cancer — kinase target scoring (CTS), regimen ranking (MDCOE/HCOS), DepMap/CPTAC validation, agentic literature discovery, and an in-development GNN-based drug-synergy predictor.

Evidence conflict audit for oncology drug target selection · 靶点尽调：七维公开证据、七条冲突规则、跨癌种比较，Python 标准库实现，零运行时依赖

Autonomous AI scientist hunting the gene dependencies childhood cancers can't live without. Every prediction is hash-locked before testing and published forever failures included.

Digital patient generation and drug response prediction via TCGA-DepMap integration — CVAE virtual patients, multi-level similarity scoring, 578-compound drug profiling

A confound-matched evaluation framework for mechanism-aware anticancer drug-synergy features (MATLAB). Reproduces the paper's tables and figures from public data.

ML pipeline linking cancer cell-line metabolomics to drug response (DepMap + GDSC).

Pharmacogenomic drug response modeling: GDSC2 × DepMap, elastic net vs XGBoost, tissue-adjusted biomarker scan, SHAP

Data from the Broad's Project Achilles synthetic-lethal screen ready for use in R.

Contradiction-aware cancer gene hypothesis triage app using public-data evidence layers.

Predicts CRISPR gene dependencies across 1,066 DepMap cancer models and ranks selective therapeutic hypotheses. Precision@10 0.965 on held-out models, validated against an independent Sanger screen.

A functional genomics framework for classifying homologous recombination deficiency and mapping PARP inhibitor sensitivity across DepMap cancer cell lines.