KBoost: a new method to infer gene regulatory networks from gene expression data.

ABSTRACT: Reconstructing gene regulatory networks is crucial to understand biological processes and holds potential for developing personalized treatment. Yet, it is still an open problem as state-of-the-art algorithms are often not able to process large amounts of data within reasonable time. Furthermore, many of the existing methods predict numerous false positives and have limited capabilities to integrate other sources of information, such as previously known interactions. Here we introduce KBoost, an algorithm that uses kernel PCA regression, boosting and Bayesian model averaging for fast and accurate reconstruction of gene regulatory networks. We have benchmarked KBoost against other high performing algorithms using three different datasets. The results show that our method compares favorably

SUBMITTER: Iglesias-Martinez LF 

PROVIDER: S-EPMC8322418 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature