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Identifying biomarkers of anti-cancer drug synergy using multi-task learning

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf00994018openalex-snapshot
Support-Vector Networks
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot
Random Forests
inferredcites →https://doi.org/10.1038/nature10868openalex-snapshot
Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR
inferredcites →https://doi.org/10.1038/nchembio817openalex-snapshot
Systems biology and combination therapy in the quest for clinical efficacy
inferredcites →https://doi.org/10.1038/srep31619openalex-snapshot
Multitask learning improves prediction of cancer drug sensitivity
inferredcites →https://doi.org/10.1093/bioinformatics/btu464openalex-snapshot
Drug susceptibility prediction against a panel of drugs using kernelized Bayesian multitask learning
inferredcites →https://doi.org/10.1093/nar/27.1.29openalex-snapshot
KEGG: Kyoto Encyclopedia of Genes and Genomes
inferredcites →https://doi.org/10.1093/nar/28.1.27openalex-snapshot
KEGG: Kyoto Encyclopedia of Genes and Genomes
inferredcites →https://doi.org/10.1093/nar/gkt1076openalex-snapshot
Data, information, knowledge and principle: back to metabolism in KEGG
inferredcites →https://doi.org/10.1109/icdar.1995.598994openalex-snapshot
Random decision forests
inferredcites →https://doi.org/10.1109/tkde.2009.191openalex-snapshot
A Survey on Transfer Learning
inferredcites →https://doi.org/10.1111/j.1467-9868.2005.00503.xopenalex-snapshot
Regularization and Variable Selection Via the Elastic Net
inferredcites →https://doi.org/10.1145/1014052.1014067openalex-snapshot
Regularized multi--task learning
inferredcites →https://doi.org/10.1152/ajpendo.00308.2012openalex-snapshot
Understanding synergy
inferredcites →https://doi.org/10.1158/0008-5472.can-11-4201openalex-snapshot
Impact of Intertumoral Heterogeneity on Predicting Chemotherapy Response of BRCA1-Deficient Mammary Tumors
inferredcites →https://doi.org/10.1371/journal.pcbi.1005308openalex-snapshot
A Computational Approach for Identifying Synergistic Drug Combinations
inferredcites →https://doi.org/10.1371/journal.pone.0061318openalex-snapshot
Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical Properties
inferredcites →https://doi.org/10.32614/cran.package.glmnetopenalex-snapshot
glmnet: Lasso and Elastic-Net Regularized Generalized Linear Models
inferredcites →https://doi.org/10.4161/cc.9.24.14326openalex-snapshot
Do predictive signatures really predict response to cancer chemotherapy?
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s12551-018-0446-zopenalex-snapshot
Machine learning and feature selection for drug response prediction in precision oncology applications
inferred← citeshttps://doi.org/10.1101/576017openalex-snapshot
Multi-task learning predicts drug combination synergy in cells and in the clinic
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