Drug Response Prediction

13 papers with code • 1 benchmarks • 1 datasets

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Most implemented papers

Variational Autoencoder for Anti-Cancer Drug Response Prediction

JIAQING-XIE/Machine-Learning-in-Genomes-Summer-Research- 22 Aug 2020

Additionally, we show that our model can generates effective drug compounds not previously used for specific cancer cell lines.

MDI+: A Flexible Random Forest-Based Feature Importance Framework

csinva/imodels 4 Jul 2023

We show that the MDI for a feature $X_k$ in each tree in an RF is equivalent to the unnormalized $R^2$ value in a linear regression of the response on the collection of decision stumps that split on $X_k$.

Learning Curves for Drug Response Prediction in Cancer Cell Lines

adpartin/dr-learning-curves 25 Nov 2020

In contrast, a GBDT with hyperparameter tuning exhibits superior performance as compared with both NNs at the lower range of training sizes for two of the datasets, whereas the mNN performs better at the higher range of training sizes.

ASGARD: A Single-cell Guided pipeline to Aid Repurposing of Drugs

lanagarmire/asgard 14 Sep 2021

Intercellular heterogeneity is a major obstacle to successful precision medicine.

AGMI: Attention-Guided Multi-omics Integration for Drug Response Prediction with Graph Neural Networks

yivan-wyygdsg/agmi 15 Dec 2021

Accurate drug response prediction (DRP) is a crucial yet challenging task in precision medicine.

Data augmentation and multimodal learning for predicting drug response in patient-derived xenografts from gene expressions and histology images

jamesdolezal/slideflow 25 Apr 2022

Prediction performance of three unimodal NNs which use GE are compared to assess the contribution of data augmentation methods.

A Fair Experimental Comparison of Neural Network Architectures for Latent Representations of Multi-Omics for Drug Response Prediction

kramerlab/multi-omics_analysis 31 Aug 2022

One important parameter is the depth of integration: the point at which the latent representations are computed or merged, which can be either early, intermediate, or late.

Prediction of drug effectiveness in rheumatoid arthritis patients based on machine learning algorithms

Gaskell-1206/Ensemble_DRP 14 Oct 2022

This study introduced a Drug Response Prediction (DRP) framework with two main goals: 1) design a data processing pipeline to extract information from tabular clinical data, and then preprocess it for functional use, and 2) predict RA patient's responses to drugs and evaluate classification models' performance.

TransEDRP: Dual Transformer model with Edge Emdedded for Drug Respond Prediction

likunnb/TransEDRP 23 Oct 2022

For the branch of cell lines genomics, we use the multi-headed attention mechanism to globally represent the genomics sequence.

Precision Anti-Cancer Drug Selection via Neural Ranking

ninglab/drugranker 30 Jun 2023

To address this, we developed neural ranking approaches that leverage large-scale drug response data across multiple cell lines from diverse cancer types.