# Multi-sample constrained network inference

Multi-sample regulatory network inference has long solved each sample separately and stitched shared structure from overlaps, which is unstable under noise. CORNETO instead solves several samples inside one mixed-integer constrained optimization with structured sparsity penalties. On haematopoietic and adult cortical single-cell data, joint inference generally improved robustness and reproducibility, while predictive gains depended on biological context and prior-network completeness.

Multi-sample regulatory network inference has long solved each sample separately and stitched shared structure from overlaps, which is unstable under noise. CORNETO instead solves several samples inside one mixed-integer constrained optimization with structured sparsity penalties. On haematopoietic and adult cortical single-cell data, joint inference generally improved robustness and reproducibility, while predictive gains depended on biological context and prior-network completeness.