Causation

The GCN captures the co-adaptive process that leads to health and aging: Consensus states emerge as a result of signaling processes that coordinate. The Generative

Cooperative Network uses consensus principles in biological signaling systems to connect "omics" data from long-lived humans and other species. Because the GCN considers biological structures to be made up of adaptive agents rather than static "omics" pieces, data can be viewed as part of a larger dynamic network from which aging emerges. This multiresolutional feedback is critical for aging causal simulation. The Data Absorption Technique is a technique in the GCN that allows you to reverse engineer these virtuous and vicious health maintenance and breakdown cycles from data, leading to treatment hypotheses.