Fig. 1: Overview of CORNETO’s framework and example applications.
From: Unifying multi-sample network inference from prior knowledge and omics data with CORNETO
CORNETO is a flexible framework that allows users to implement and extend diverse network inference methods by reformulating them as constrained optimization problems. For any method, the process begins by mapping omics data (for example, transcriptomics or proteomics) onto PKNs, which can vary in complexity from simple interaction graphs to detailed metabolic networks. CORNETO then reformulates the method into a specific optimization problem, ensuring that it can be optimally solved using mathematical programming techniques. A key contribution of CORNETO is its ability to enable joint inference across multiple samples, leveraging shared patterns to improve network inference. Using this framework, we have extended several methods and demonstrated their effectiveness in diverse biological use cases. Figure adapted from ref. 14 (Fig. 2) under a Creative Commons license CC-BY 4.0.
