Predicting anticancer synergistic drug combinations based on multi-task learning.

ABSTRACT:

Background

The discovery of anticancer drug combinations is a crucial work of anticancer treatment. In recent years, pre-screening drug combinations with synergistic effects in a large-scale search space adopting computational methods, especially deep learning methods, is increasingly popular with researchers. Although achievements have been made to predict anticancer synergistic drug combinations based on deep learning, the application of multi-task learning in this field is relatively rare. The successful practice of multi-task learning in various fields shows that it can effectively learn multiple tasks jointly and improve the performance of all the tasks.

Methods

In this paper, we propose MTLSynergy which is based on multi-task learning and deep neural networks to predic

SUBMITTER: Chen D 

PROVIDER: S-EPMC10680313 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature