Decoding neuronal gene expression: integrative insights from omics and AI
Abstract
Neuronal functional diversity and pathological vulnerability are governed by multi-layered regulatory programs. While high-throughput omics and neuroimaging provide high-resolution snapshots of these programs, bridging the gap between molecular dynamics and macro-scale brain architecture remains a significant informatics challenge. This review synthesizes the evolution of computational frameworks in neuro-omics-transitioning from descriptive co-expression modules to causal graph neural networks and cross-scale foundation models. We evaluate these methodologies within the context of Alzheimer's disease, schizophrenia, and epilepsy, identifying critical bottlenecks in data harmonization, spatial alignment, and causal interpretability.
Fields of Study & Subjects
Gene Regulatory Network Analysis
Bioinformatics and Genomic Networks
Cell Image Analysis Techniques
Publication details
- Journal / source
- Brain Informatics
- Publisher
- Springer Science and Business Media LLC
- Volume
- 13
- Issue
- 1
- Publication date
- 21 July 2026
- Language
- EN