ArticleBMC bioinformatics2019
Parallelisation strategies for agent based simulation of immune systems.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- BMX: Biological modelling and interface exchange.Scientific reports · 2023Article
- An agent-based approach for modelling and simulation of glycoprotein VI receptor diffusion, localisation and dimerisation in platelet lipid rafts.Scientific reports · 2023Article
- In Silico Studies to Support Vaccine Development.Pharmaceutics · 2023Review
- Cancer immune control dynamics: a clinical data driven model of systemic immunity in patients with metastatic melanoma.BMC bioinformatics · 2021Article
- Toward computational modelling on immune system function.BMC bioinformatics · 2019Article
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Authors and funding
5 authors.
Funding
Abstract
backgroundIn recent years, the study of immune response behaviour using bottom up approach, Agent Based Modeling (ABM), has attracted considerable efforts. The ABM approach is a very common technique in the biological domain due to high demand for a large scale analysis tools for the collection and interpretation of information to solve biological problems. Simulating massive multi-agent systems (i.e. simulations containing a large number of agents/entities) requires major computational effort which is only achievable through the use of parallel computing approaches.
resultsThis paper explores different approaches to parallelising the key component of biological and immune system models within an ABM model: pairwise interactions. The focus of this paper is on the performance and algorithmic design choices of cell interactions in continuous and discrete space where agents/entities are competing to interact with one another within a parallel environment.
conclusionsOur performance results demonstrate the applicability of these methods to a broader class of biological systems exhibiting typical cell to cell interactions. The advantage and disadvantage of each implementation is discussed showing each can be used as the basis for developing complete immune system models on parallel hardware.
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