In silico biology : making the most of parallel computing
Contribuinte(s) |
Lazakidou, Athina |
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Data(s) |
2009
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Resumo |
Biological systems are typically complex and adaptive, involving large numbers of entities, or organisms, and many-layered interactions between these. System behaviour evolves over time, and typically benefits from previous experience by retaining memory of previous events. Given the dynamic nature of these phenomena, it is non-trivial to provide a comprehensive description of complex adaptive systems and, in particular, to define the importance and contribution of low-level unsupervised interactions to the overall evolution process. In this chapter, the authors focus on the application of the agent-based paradigm in the context of the immune response to HIV. Explicit implementation of lymph nodes and the associated lymph network, including lymphatic chain structure, is a key objective, and requires parallelisation of the model. Steps taken towards an optimal communication strategy are detailed. |
Formato |
application/pdf |
Identificador | |
Publicador |
IGI Global |
Relação |
http://eprints.qut.edu.au/82663/1/82663.pdf DOI:10.4018/978-1-60566-768-3.ch003 Perrin, Dimitri, Ruskin, Heather J, & Crane, Martin (2009) In silico biology : making the most of parallel computing. In Lazakidou, Athina (Ed.) Biocomputation and Biomedical Informatics : Case Studies and Applications. IGI Global, pp. 55-74. |
Direitos |
Copyright 2009 IGI Global |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Tipo |
Book Chapter |