ReviewBriefings in bioinformatics2021
Drug sensitivity prediction from cell line-based pharmacogenomics data: guidelines for developing machine learning models.
Review in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
36 citing papers in PubMed, 60 citations in OpenAlex.
- Predicting gene essentiality and drug response from preclinical perturbation screens with layered ensemble of autoencoders and predictors.Scientific reports · 2026Article
- Discovery of predictive biomarkers for cancer therapy through computational approaches.Nature reviews. Clinical oncology · 2026Review
- Benchmarking community drug response prediction models: datasets, models, tools, and metrics for cross-dataset generalization analysis.Briefings in bioinformatics · 2026Article
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- A RAIR-ATC transcriptional axis and multimodal drug-response modelling reveal class-level vulnerabilities in thyroid cancer.Frontiers in pharmacology · 2026Article
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- Exploring Artificial Intelligence's Potential to Enhance Conventional Anticancer Drug Development.Drug development research · 2025Review
- Interpretable Transfer Learning for Cancer Drug Resistance: Candidate Target Identification.Current issues in molecular biology · 2025Article
- CellHit: a web server to predict and analyze cancer patients' drug responsiveness.Nucleic acids research · 2025Article
- Understanding the sources of performance in deep drug response models reveals insights and improvements.Bioinformatics (Oxford, England) · 2025Article
- Biomarker-Driven Approaches to Bone Metastases: From Molecular Mechanisms to Clinical Applications.Biomedicines · 2025Review
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- Wnt signaling in cancer: from biomarkers to targeted therapies and clinical translation.Molecular cancer · 2025Review
- The specification game: rethinking the evaluation of drug response prediction for precision oncology.Journal of cheminformatics · 2025Article
- Learning and actioning general principles of cancer cell drug sensitivity.Nature communications · 2025Article
- Pan-Cancer Drug Sensitivity Prediction from Gene Expression using Deep Learning.bioRxiv : the preprint server for biology · 2024Article
- Trust me if you can: a survey on reliability and interpretability of machine learning approaches for drug sensitivity prediction in cancer.Briefings in bioinformatics · 2024Review
- Reliable anti-cancer drug sensitivity prediction and prioritization.Scientific reports · 2024Article
- Overcoming limitations in current measures of drug response may enable AI-driven precision oncology.NPJ precision oncology · 2024Article
- Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
The goal of precision oncology is to tailor treatment for patients individually using the genomic profile of their tumors. Pharmacogenomics datasets such as cancer cell lines are among the most valuable resources for drug sensitivity prediction, a crucial task of precision oncology. Machine learning methods have been employed to predict drug sensitivity based on the multiple omics data available for large panels of cancer cell lines. However, there are no comprehensive guidelines on how to properly train and validate such machine learning models for drug sensitivity prediction. In this paper, we introduce a set of guidelines for different aspects of training gene expression-based predictors using cell line datasets. These guidelines provide extensive analysis of the generalization of drug sensitivity predictors and challenge many current practices in the community including the choice of training dataset and measure of drug sensitivity. The application of these guidelines in future studies will enable the development of more robust preclinical biomarkers.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.