A network-based trans-omics approach for predicting synergistic drug combinations.

ABSTRACT:

Background

Combination therapy can offer greater efficacy on medical treatments. However, the discovery of synergistic drug combinations is challenging. We propose a novel computational method, SyndrumNET, to predict synergistic drug combinations by network propagation with trans-omics analyses.

Methods

The prediction is based on the topological relationship, network-based proximity, and transcriptional correlation between diseases and drugs. SyndrumNET was applied to analyzing six diseases including asthma, diabetes, hypertension, colorectal cancer, acute myeloid leukemia (AML), and chronic myeloid leukemia (CML).

Results

Here we show that SyndrumNET outperforms the previous methods in terms of high accuracy. We perform in vitro cell survival assays to validate our p

SUBMITTER: Iida M 

PROVIDER: S-EPMC11286857 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature