Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.

ABSTRACT: Despite the widespread availability of genome sequencing pipelines, many genes remain part of the genome's "dark matter," where existing inference tools cannot even begin to guess the biological function of their proteins from sequence alone. This challenge is especially pronounced in organisms that are highly evolutionarily distant from well-studied models, where homology-based methods break down. Here, we describe PHILHARMONIC, a computational method that combines deep learning-based de novo protein interaction network inference with robust unsupervised spectral clustering and remote homology to illuminate functional organization in any non-model organism. From only a sequenced proteome, we show PHILHARMONIC predicts protein functions, functional communities, and higher-order netw

SUBMITTER: Sledzieski S 

PROVIDER: S-EPMC11565725 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature