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For example, high [[determinism]]  in gene expression networks can be understood as one gene almost certainly leading to the expression of another gene. High [[degeneracy]] is also prevalent in biological systems throughout evolution. These two factors make it unclear at what scale biological systems should be analyzed to better understand their functions. Klein et al. <ref>Klein B, Hoel E, Swain A, et al. Evolution and emergence: higher order information structure in protein interactomes across the tree of life[J]. Integrative Biology, 2021, 13(12): 283-294.</ref> analyzed [[protein interaction networks]] of more than 1800 species and found that networks at macroscopic scales have less noise and [[degeneracy]]. At the same time, compared with nodes that do not participate in macroscopic scales, nodes in macroscopic scale networks are more resilient. Therefore, in order to meet the requirements of evolution, biological networks need to evolve macroscopic scales to increase certainty to enhance [[network resilience]] and improve the effectiveness of information transmission.

For example, high [[determinism]]  in gene regulatory networks (GRN) can be understood as one gene almost certainly leading to the expression of another gene. High [[degeneracy]] is also prevalent in biological systems throughout evolution. These two factors make it unclear at what scale biological systems should be analyzed to better understand their functions. Klein et al. <ref>Klein B, Hoel E, Swain A, et al. Evolution and emergence: higher order information structure in protein interactomes across the tree of life[J]. Integrative Biology, 2021, 13(12): 283-294.</ref> analyzed [[protein interaction networks]] of more than 1800 species and found that networks at macroscopic scales have less noise and [[degeneracy]]. At the same time, compared with nodes that do not participate in macroscopic scales, nodes in macroscopic scale networks are more resilient. Therefore, in order to meet the requirements of evolution, biological networks need to evolve macroscopic scales to increase certainty to enhance [[network resilience]] and improve the effectiveness of information transmission.

Swain et al. in the article <ref>Swain A, Williams S D, Di Felice L J, et al. Interactions and information: exploring task allocation in ant colonies using network analysis[J]. Animal Behaviour, 2022, 18969-81.</ref> explored the influence of the interaction history of ant colonies on task allocation and task switching, and used effective information to study how noise spreads among ants. The results indicate that historical interactions between ant colonies affects task allocation, while specific interaction types determine noise levels. In addition, even when ants switch functional groups, the emergent cohesion of ant colonies can ensure the stability of the colony. At the same time, different functional ant colonies also play different roles in maintaining the cohesion of the colony.

Swain et al. in the article <ref>Swain A, Williams S D, Di Felice L J, et al. Interactions and information: exploring task allocation in ant colonies using network analysis[J]. Animal Behaviour, 2022, 18969-81.</ref> explored the influence of the interaction history of ant colonies on task allocation and task switching, and used effective information to study how noise spreads among ants. The results indicate that historical interactions between ant colonies affects task allocation, while specific interaction types determine noise levels. In addition, even when ants switch functional groups, the emergent cohesion of ant colonies can ensure the stability of the colony. At the same time, different functional ant colonies also play different roles in maintaining the cohesion of the colony.

===Application on artificial neural networks===

===Application on artificial neural networks===