comboLTR: Modeling drug combination effects via latent tensor reconstruction
Overview
comboLTR is a new polynomial regression-based framework for modeling anti-cancer effects of drug combinations in various doses and across different cancer cell lines. It is implemented in Python.
The data used in the experiments is available on: https://doi.org/10.5281/zenodo.4625084.
Instructions
ltr_tensor_solver_actxu_v_cls_010.py This file contains the code for polynomial regression via latent tensor reconstruction.
The description of the interface of the solver is given in readme.pdf file.
comboLTR_CV.py This file contains the code for cross validations on the full dataset used in the paper.
Dependencies
- numpy
- scikit-learn
- scipy