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首页> 外文期刊>BMC Medical Informatics and Decision Making >Optimal vaccination schedule search using genetic algorithm over MPI technology
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Optimal vaccination schedule search using genetic algorithm over MPI technology

机译：基于MPI技术的遗传算法最优疫苗接种时间表搜索

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Background Immunological strategies that achieve the prevention of tumor growth are based on the presumption that the immune system, if triggered before tumor onset, could be able to defend from specific cancers. In supporting this assertion, in the last decade active immunization approaches prevented some virus-related cancers in humans. An immunopreventive cell vaccine for the non-virus-related human breast cancer has been recently developed. This vaccine, called Triplex, targets the HER-2-neu oncogene in HER-2eu transgenic mice and has shown to almost completely prevent HER-2eu-driven mammary carcinogenesis when administered with an intensive and life-long schedule. Methods To better understand the preventive efficacy of the Triplex vaccine in reduced schedules we employed a computational approach. The computer model developed allowed us to test in silico specific vaccination schedules in the quest for optimality. Specifically here we present a parallel genetic algorithm able to suggest optimal vaccination schedule. Results & Conclusions The enormous complexity of combinatorial space to be explored makes this approach the only possible one. The suggested schedule was then tested in vivo, giving good results. Finally, biologically relevant outcomes of optimization are presented.
机译：背景技术能够预防肿瘤生长的免疫策略是基于这样的假设，即免疫系统如果在肿瘤发作之前被触发，就能够防御特定的癌症。为了支持这一主张，在过去的十年中，主动免疫方法预防了人类中某些病毒相关的癌症。最近已经开发出用于与病毒无关的人类乳腺癌的免疫预防细胞疫苗。这种疫苗称为Triplex，以HER-2 / neu转基因小鼠中的HER-2-neu癌基因为靶标，并已显示出在密集且终身使用的情况下几乎可以完全预防HER-2 / neu驱动的乳腺癌致癌作用。方法为了更好地了解三联疫苗在减少的时间表中的预防效果，我们采用了一种计算方法。开发的计算机模型使我们能够在计算机模拟中测试特定的疫苗接种计划，以求达到最佳效果。特别是在这里，我们提出一种能够建议最佳疫苗接种时间表的并行遗传算法。结果与结论组合空间的巨大复杂性使其成为唯一可行的方法。然后对建议的时间表进行了体内测试，得出了良好的结果。最后，提出了生物学相关的优化结果。

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