Functional profiling of the sequence stockpile: a protein pair-based assessment of in silico prediction tools.

ABSTRACT:

Motivation

In silico functional annotation of proteins is crucial to narrowing the sequencing-accelerated gap in our understanding of protein activities. Numerous function annotation methods exist, and their ranks have been growing, particularly so with the recent deep learning-based developments. However, it is unclear if these tools are truly predictive. As we are not aware of any methods that can identify new terms in functional ontologies, we ask if they can, at least, identify molecular functions of proteins that are non-homologous to or far-removed from known protein families.

Results

Here, we explore the potential and limitations of the existing methods in predicting the molecular functions of thousands of such proteins. Lacking the "ground truth" functional annotatio

SUBMITTER: Prabakaran R 

PROVIDER: S-EPMC11821270 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature