A variational expectation-maximization framework for balanced multi-scale learning of protein and drug interactions.

ABSTRACT: Protein functions are characterized by interactions with proteins, drugs, and other biomolecules. Understanding these interactions is essential for deciphering the molecular mechanisms underlying biological processes and developing new therapeutic strategies. Current computational methods mostly predict interactions based on either molecular network or structural information, without integrating them within a unified multi-scale framework. While a few multi-view learning methods are devoted to fusing the multi-scale information, these methods tend to rely intensively on a single scale and under-fitting the others, likely attributed to the imbalanced nature and inherent greediness of multi-scale learning. To alleviate the optimization imbalance, we present MUSE, a multi-scale representation

SUBMITTER: Rao J 

PROVIDER: S-EPMC11530528 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature