Article

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile Data

2020-12-22

Abstract excerpt

The Columbia Cancer Target Discovery and Development (CTD 2 ) Center has developed PANACEA (PANcancer Analysis of Chemical Entity Activity), a collection of dose-response curves and perturbational profiles for 400 clinical oncology drugs in cell lines selected to optimally represent 19 cancer subtypes. This resource, developed to study tumor-specific drug mechanism of action, was instrumental in hosting a DREAM C...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: f8f18c2c-e135-5ec4-92bb-ad6ea276f671
DOI: 10.1101/2020.12.21.423514

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Community Challenge for Pancancer Drug Mechanism of Action Inference from Perturbational Profile DataDOI 10.1101/2020.12.21.423514Read

UniCure: A Foundation Model for Predicting Personalized Cancer Therapy ResponseSemantic proximity Read

BKDRP: A Biological Knowledge-Driven Approach for Drug Response Prediction Using Multi-Omics Data in Cancer Cell LinesSemantic proximity Read

A network model for patient-derived drug response in breast cancer integrating multi-omics datasetsSemantic proximity Read

A cancer pharmacogenomic screen powering crowd-sourced advancement of drug combination predictionSemantic proximity Read

Cancer Cell Line Heterogeneity Imposes a Primary Bottleneck for Virtual Perturbation Screening at ScaleSemantic proximity Read

Dose-dependent modeling of combinatorial drug responses stratifies patient survival and reveals therapeutic vulnerabilities in precision oncologySemantic proximity Read

Computational Advancements in Cancer Combination Therapy PredictionSemantic proximity Read

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapiesSemantic proximity Read

Deep characterization of cancer drugs mechanism of action by integrating large-scale genetic and drug screensSemantic proximity Read

Personalized Cancer Therapy Prioritization Based on Driver Alteration Co-occurrence PatternsSemantic proximity Read

Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep LearningSemantic proximity Read

A precision oncology-focused deep learning framework for personalized selection of cancer therapySemantic proximity Read