What you need to process the Quarterly DepMap-Omics releases from Terra
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Updated
Jul 17, 2026 - HTML
What you need to process the Quarterly DepMap-Omics releases from Terra
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
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 CTS extension and dependency-prediction ML model
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
ML pipeline linking cancer cell-line metabolomics to drug response (DepMap + GDSC).
Digital patient generation and drug response prediction via TCGA-DepMap integration — CVAE virtual patients, multi-level similarity scoring, 578-compound drug profiling
Pharmacogenomic drug response modeling: GDSC2 × DepMap, elastic net vs XGBoost, tissue-adjusted biomarker scan, SHAP
Stability and counterfactual audit of motif-level explanations in cell-conditioned multi-omics drug response prediction: pipeline, processed GDSC2 x DepMap data and results
A signed readout of organelle dynamics — biogenesis minus selective clearance — from ordinary expression data. Predicts mitochondrial drug and genetic vulnerability across 1,066 cancer cell lines.
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.
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