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Computational biological models have proven to be an invaluable tool for understanding and predicting the behaviour of many biological systems. While it may not be too challenging for experienced researchers to construct such models from scratch, it is not a straightforward task for early stage researchers. Design patterns are well-known techniques widely applied in software engineering as they provide a set of typical solutions to common problems in software design. In this paper, we collect and discuss common patterns that are usually used during the construction and execution of computational biological models. We adopt Petri nets as a modelling language to provide a visual illustration of each pattern; however, the ideas presented in this paper can also be implemented using other modelling formalisms. We provide two case studies for illustration purposes and show how these models can be built up from the presented smaller modules. We hope that the ideas discussed in this paper will help many researchers in building their own future models. [ABSTRACT FROM AUTHOR]

Epigenetics in the form of DNA methylation and other processes is an established property of genotypes and a focus of empirical research. Yet, there remain fundamental gaps in the evolutionary theory of epigenetics. To support a comprehensive understanding of epigenetics, this paper investigates theoretically the combined effects of deleterious mutation and epimutation with and without inbreeding. Both spontaneous epimutation and paramutation are considered to cover a broader range of epigenetic phenomena. We find that inbreeding generally reduces the amount of segregating deleterious genetic and epigenetic variation at equilibrium, although interestingly inbreeding can also increase the amount of deleterious genetic or epigenetic variation. Furthermore, we also demonstrate that epimutation indirectly can cause increased or decreased deleterious genetic variation at equilibrium relative to classic expectations, which is particularly evident when paramutation is occurring. With the addition of deleterious epimutation, there may be significantly increased purging of deleterious variation in more inbred populations and a significantly increased amount of segregating deleterious variation in more outbred populations, with notable exceptions. [ABSTRACT FROM AUTHOR]

A computational human brain model with the voxel-wise assimilation method was established based on individual structural and functional imaging data. We found that the more similar the brain model is to the biological counterpart in both scale and architecture, the more similarity was found between the assimilated model and the biological brain both in resting states and during tasks by quantitative metrics. The hypothesis that resting state activity reflects internal body states was validated by the interoceptive circuit's capability to enhance the similarity between the simulation model and the biological brain. We identified that the removal of connections from the primary visual cortex (V1) to downstream visual pathways significantly decreased the similarity at the hippocampus between the model and its biological counterpart, despite a slight influence on the whole brain. In conclusion, the model and methodology present a solid quantitative framework for a digital twin brain for discovering the relationship between brain architecture and functions, and for digitally trying and testing diverse cognitive, medical and lesioning approaches that would otherwise be unfeasible in real subjects. [ABSTRACT FROM AUTHOR]