Bind: large-scale biological interaction network discovery through knowledge graph-driven machine learning.

ABSTRACT:

Background

Biological systems derive from complex interactions between entities ranging from biomolecules to macroscopic structures, forming intricate networks essential for understanding disease mechanisms and developing therapeutic interventions. Current AI-driven interaction predictors typically operate in isolation, focusing on single tasks and missing the broader picture of how different biological interactions influence each other. Traditional wet-lab approaches for identifying these interactions are expensive, time-consuming, and error-prone. No unified platform currently exists where biologists can predict and analyze multiple types of biological relationships comprehensively, limiting our ability to discover new therapeutic applications and fully understand interconnected

SUBMITTER: Aamer N 

PROVIDER: S-EPMC12315434 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature