Dynamic Models and Discrete Event Simulation

Delaney, William V.; Vaccari, Eugenio

doi:10.1201/9781003065692

Cited by 16 publications

(4 citation statements)

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“…The growth of a network evolving at discrete temporal intervals can be modeled with Discrete Event Simulation (DES) tools [23][24][25] . Borrowing the DES rationale, we modeled the evolution of directed networks of domain organization with time flowing from one event to another as discrete evolutionary 'time steps', typical of a step function.…”

Section: (Iii) Time Event-based 'Radial' and 'Waterfall' Layoutsmentioning

confidence: 99%

Evolution of Networks of Protein Domain Organization

Aziz

Caetano‐Anollés

2020

Preprint

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Domains are the structural, functional and evolutionary units of proteins. They combine to form multidomain proteins. The evolutionary history of this molecular combinatorics has been studied with phylogenomic methods. Here, we construct networks of domain organization and explore their evolution. These networks revealed two ancient waves of structural novelty arising from ancient ‘p-loop’ and ‘winged helix’ domains and a massive ‘big bang’ of domain organization. The evolutionary recruitment of domains was highly modular, hierarchical and ongoing. Domain rearrangements elicited non-random and scale-free network structure. Comparative analyses of preferential attachment, randomness and modularity of networks showed yin-and-yang complementary transition patterns along the evolutionary timeline. Remarkably, evolving networks highlighted a central evolutionary role of cofactor-supporting structures of non-ribosomal peptide synthesis (NRPS) pathways, likely crucial to the early development of the genetic code. Some highly modular domains featured dual response regulation in two-component signal transduction systems with DNA-binding activity linked to transcriptional regulation of responses to environmental change. Interestingly, hub domains across the evolving networks shared the historical role of DNA binding and editing, an ancient protein function in molecular evolution. Our investigation unfolds historical source-sink patterns of evolutionary recruitment that further our understanding of protein architectures and functions.

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Section: (Iii) Time Event-based 'Radial' and 'Waterfall' Layoutsmentioning

confidence: 99%

Evolution of Networks of Protein Domain Organization

Aziz

Caetano‐Anollés

2020

Preprint

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“…Evolving networks can be modeled using computer-based Discrete Event Simulation (DES) tools [35][36][37] . DES tools delineate the growth and behavior of complex networks as a sequence of discrete events, with time flowing from event to event as a step function.…”

Section: Reconstructing the History Of An 'Elementary Functionome' Of...mentioning

confidence: 99%

Tracing the birth of structural domains from loops during protein evolution

Aziz

Mughal

Caetano‐Anollés

2023

Preprint

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The structures and functions of proteins are embedded into the loop scaffolds of structural domains. Their origin and evolution remain mysterious. Here, we use a novel graph-theoretical approach to describe how modular and non-modular loop prototypes combine to form folded structures in protein domain evolution. Phylogenomic data-driven chronologies reoriented a bipartite network of loops and domains (and its projections) into ‘waterfalls’ depicting an evolving ‘elementary functionome’ (EF). Two primordial waves of functional innovation involving founder ‘p-loop’ and ‘winged-helix’ domains were accompanied by an ongoing emergence and reuse of structural and functional novelty. Metabolic pathways expanded before translation functionalities. A dual hourglass recruitment pattern transferred scale-free properties from loop to domain components of the EF network in generative cycles of hierarchical modularity. Modeling the evolutionary emergence of the oldest P-loop and winged-helix domains with AlphFold2 uncovered rapid convergence towards folded structure, suggesting that a folding vocabulary exists in loops for protein fold repurposing and design.

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“…It is usually difficult to construct analytic models to represent such complex environments (Fishwick, 1995). AWESIM is a discrete event simulation model that changes its state each time a new event occurs (Delaney and Vaccari, 1989). The simulation approach is based on the description of the series of events that occur in ‫عشر‬ ‫الثالث‬ ‫المجلد‬ ‫الثاني‬ ‫العدد‬ -‫إبريل‬ 2222 425 sequence, in order to replicate the system behavior.…”

Section: Simulating the Hospital Patient Flowmentioning

confidence: 99%

A Proposed Management Information System for Managing Hospital Resources Using Simulation Researchers

Mosallam

Eisa²

2022

المجلة العلمیة للدراسات التجاریة والبیئیة

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A hospital environment is a complex system that requires appropriate allocation of human and material resources in order to optimize its effectiveness and efficiency. This paper utilizes a simulation model to investigate patients' flow in a hospital, and how the resources are utilized to respond to the health care system. Results of the study provide insight to the management as to how the patient, doctors, paramedics and other non-clinical resources compete to respond to the health care needs. As an example of how to reduce patients' queue time, the administrator may use the response surface results

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Dynamic Models and Discrete Event Simulation

Cited by 16 publications

References 0 publications

Evolution of Networks of Protein Domain Organization

Evolution of Networks of Protein Domain Organization

Tracing the birth of structural domains from loops during protein evolution

A Proposed Management Information System for Managing Hospital Resources Using Simulation Researchers

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