PWN: enhanced random walk on a warped network for disease target prioritization.

ABSTRACT:

Background

Extracting meaningful information from unbiased high-throughput data has been a challenge in diverse areas. Specifically, in the early stages of drug discovery, a considerable amount of data was generated to understand disease biology when identifying disease targets. Several random walk-based approaches have been applied to solve this problem, but they still have limitations. Therefore, we suggest a new method that enhances the effectiveness of high-throughput data analysis with random walks.

Results

We developed a new random walk-based algorithm named prioritization with a warped network (PWN), which employs a warped network to achieve enhanced performance. Network warping is based on both internal and external features: graph curvature and prior knowledge.

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SUBMITTER: Han S 

PROVIDER: S-EPMC10031933 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature