Article

Predicting Cancer Drug Response Using a Recommender System

2017-11-07

Abstract excerpt

<h4>Motivation</h4> As we move towards an era of precision medicine, the ability to predict patient-specific drug responses in cancer based on molecular information such as gene expression data represents both an opportunity and a challenge. In particular, methods are needed that can accommodate the high-dimensionality of data to learn interpretable models capturing drug response mechanisms, as well as providing...

Topics

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

Identifiers and source

Literature Corpus work: c0936b4f-1317-5985-bcd1-a1a35e4601aa
DOI: 10.1101/215327

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting Cancer Drug Response Using a Recommender SystemDOI 10.1101/215327Read

Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell linesSemantic proximity Read

A Personalized Cancer Drug Recommendation System with Machine LearningSemantic proximity Read

ANTENNA, a Multi-Rank, Multi-Layered Recommender System for Inferring Reliable Drug-Gene-Disease Associations: Repurposing Diazoxide as a Targeted Anti-Cancer TherapySemantic proximity Read

A Survey and Systematic Assessment of Computational Methods for Drug Response PredictionSemantic proximity Read

DruID: Personalized <b>Dru</b> g Recommendations by <b>I</b> ntegrating Multiple Biomedical <b>D</b> atabases for CancerSemantic proximity Read

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

BioXNet: a biologically inspired neural network for deciphering anti-cancer drug response in precision medicineSemantic proximity Read

Joint Prediction of Adjuvant Therapy Response and Time-to-Response for Cancer Patients Using the Personalized-DrugRank MethodSemantic proximity Read

Looking at the BiG picture: Incorporating bipartite graphs in drug response predictionSemantic proximity Read

A Pan-Cancer, Pan-Treatment (PCPT) Model For Predicting Drug Responses From Patient-Derived Xenografts With Application To Cancer Types With Sparse Training DataSemantic proximity Read

Mining drug-disease relationships as a complement to medical genetics-based drug repositioning: Where a recommendation system meets genome-wide association studies.Semantic proximity Read

DBPOM: a comprehensive database of pharmaco-omics for cancer precision medicineSemantic proximity Read