Article

A regularized functional regression model enabling transcriptome-wide dosage-dependent association study of cancer drug response

2020-06-18

Abstract excerpt

Cancer treatments can be highly toxic and frequently only a subset of the patient population will benefit from a given treatment. Tumour genetic makeup plays an important role in cancer drug sensitivity. We suspect that gene expression markers could be used as a decision aid for treatment selection or dosage tuning. Using in vitro cancer cell line dose-response and gene expression data from the Genomics of Drug S...

Topics

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

Identifiers and source

Literature Corpus work: 12bf8a40-f2df-589c-93dc-13e542e96b3d
DOI: 10.1101/2020.06.18.158907

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A regularized functional regression model enabling transcriptome-wide dosage-dependent association study of cancer drug responseDOI 10.1101/2020.06.18.158907Read

Dr.Paso: Drug response prediction and analysis system for oncology researchSemantic proximity Read

Identifying anti-cancer drug response related genes using an integrative analysis of transcriptomic and genomic variations with cell line-based drug perturbations.Semantic proximity Read

Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical modelsSemantic proximity Read

Genetic dose-response modelling predicts drug mechanisms, dosing, and adverse eventsSemantic proximity Read

Drug Sensitivity Prediction From Cell Line-Based Pharmacogenomics Data: Guidelines for Developing Machine Learning ModelsSemantic proximity Read

Systematic assessment of multi-gene predictors of pan-cancer cell line sensitivity to drugs exploiting gene expression dataSemantic proximity Read

A Deep Learning Framework for Prediction of Clinical Drug Response of Cancer Patients and Identification of Drug Sensitivity Biomarkers using Preclinical SamplesSemantic proximity Read

Cancer drug sensitivity prediction from routine histology imagesSemantic proximity Read

Biomarker identification for statin sensitivity of cancer cell linesSemantic proximity Read

Inferring tumor-specific cancer dependencies through integrating ex vivo drug response assays and drug-protein profiling.Semantic proximity Read

From Hype to Health Check: Critical Evaluation of Drug Response Prediction Models with DrEvalSemantic proximity Read

Linking drug target and pathway activation for effective therapy using multi-task learningSemantic proximity Read