Advanced computing for systems biology
Advanced computing for systems biology
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DOI：
10.1093/bib/bbl033
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发表时间：
2006-12-01
影响因子：
9.5
通讯作者：
Ragan, Mark A.
中科院分区：
文献类型：
--
作者：
Burrage, Kevin;Hood, Lindsay;Ragan, Mark A.
系统生物学是基于对相互作用的组件的大型网络的计算建模和模拟。模型的目的可能是在不同的保真度水平上捕捉过程、机制、组成部分和相互作用。输入数据通常很大，并且在地理上分散，并且可能需要将计算移动到数据，而不是相反。此外，复杂的系统级问题需要跨机构和跨学科的协作。网格计算可以为分布式数据、计算和专业知识提供健壮的、可扩展的解决方案。我们说明了一些系统生物学的计算和数据要求的范围与三个案例研究：一个需要大量的计算，但小数据（比较基因组学中的同源映射），第二个涉及复杂的TB级数据（可见细胞项目）和第三个是计算和数据密集型（模拟在多个时间和空间尺度）。认证、授权和审计系统目前的可扩展性不好，可能会成为分布式协作的瓶颈，特别是在成果可能商业化的情况下。挑战仍然是提供轻量级的标准，以促进强大的，可扩展的网格类型的计算渗透到不同的用户社区，以满足不断变化的需求系统生物学。
Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.