InterLabelGO+: unraveling label correlations in protein function prediction.

ABSTRACT:

Motivation

Accurate protein function prediction is crucial for understanding biological processes and advancing biomedical research. However, the rapid growth of protein sequences far outpaces the experimental characterization of their functions, necessitating the development of automated computational methods.

Results

We present InterLabelGO+, a hybrid approach that integrates a deep learning-based method with an alignment-based method for improved protein function prediction. InterLabelGO+ incorporates a novel loss function that addresses label dependency and imbalance and further enhances performance through dynamic weighting of the alignment-based component. A preliminary version of InterLabelGO+ achieved a strong performance in the CAFA5 challenge, ranking sixth out of

SUBMITTER: Liu Q 

PROVIDER: S-EPMC11568131 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature