Observational analysis integrates emergence in health data during COVID-19, highlighting a new data management approach.
This manuscript is dedicated to the concept of emergence in modern systems biology and discusses the essence of this concept, its role, and its implementation using the example of epidemic modeling for COVID-19, where three dimensions of emergence should be integrated: (i) the emergence of the epidemic and the spread of the virus in a population from interactions between susceptible, infected, and recovered individuals; (ii) the emergence of health-related properties of one individual from interactions between biomolecules; (iii) the emergence of the research project from interactions between various institutions collecting different pieces of clinical data. Systems biological understanding of biological emergence may require changes in data management approaches. By adding the concept of Emergence, classical FAIR data management may be extended to FAIRE, where data become not only Findable, Accessible, Interoperable, and Reusable, but also Emergeable (FAIRE). To implement FAIRE data management, we propose a Silicon Organism Model-Engrossed Data Integration approach (SOMEDAI), where data are not just stored in separate databases, but are integrated into a mathematical model. The latter allows for validating data consistency and using the data to reconstruct the emergent behaviour of the whole system.
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Alexey Kolodkin (2025) studied this question.
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