Biologically informed neural network models are robust to spurious interactions via self-pruning.

ABSTRACT: Computational models of cellular networks hold promise to uncover disease mechanisms and guide therapeutic strategies. Biology-informed neural networks (BINNs) is an emerging approach to create such models by combining the predictive power of deep learning with prior knowledge, a vital aspect of biological research. The architectures of BINN's enforces a network structure from which mechanism can ideally be inferred. However, a key challenge is to evaluate the reliability of these mechanisms, as cells are inherently complex, involving intricate and sometimes unknown interactions. Currently, analysis mainly focuses on selected pathways rather than a more comprehensive perspective. In this work we demonstrate an improved, holistic approach: we measure to which extent purposefully introduced

SUBMITTER: Nordenstorm O 

PROVIDER: S-EPMC12636328 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature