利用网格技术解决禽流感问题的创新计算机方法
Innovative in silico approaches to address avian flu using grid technology
摘要：
近年来出现了一些疾病，这些疾病通过人类旅行（如SARS）或动物迁徙（如禽流感）在世界各地迅速传播。在传染性新兴疾病提出的最大挑战中，一个是与病毒的不断突变有关，这使它们成为药物和疫苗发现的不断移动的目标。另一个挑战涉及疾病的早期发现和监测，因为由于交流的全球化以及人和动物在地球上的流动，新的病例可能出现在任何地方，最近的禽流感流行病就是证明。三年来，欧洲和亚洲的团队一直在探索一些创新的计算机方法，以更好地利用国际网格基础设施上的巨大计算资源来应对禽流感。网格被用来研究突变对现有抗H5N1药物有效性的影响，并寻找对突变菌株有活性的潜在新线索。网格还允许以完全安全的方式集成分布式数据。本文介绍了我们目前正在探索如何将现有的数据源整合到全球分子流行病学监测网络中。
英文摘要：
The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
