ITR: Self-Replicative Information Processing

ITR：自我复制信息处理

• 批准号: 0313214
• 负责人: John Yin
• 金额: $ 42万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2006-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0313214&HistoricalAwards=false
• 关键词: ITR; Self; Replicative; Information; Processing

In nature, viruses are self-replicating entities that differ from one another in their genomic makeup (RNA or DNA), their genome sizes (spanning two orders of magnitude), and their host-ranges (spanning all kingdoms of life), yet all viruses share the need to express their own genome-encoded functions as mRNA, direct the synthesis of their proteins using the translation machinery of their host, copy their genomes, and assemble their resulting progeny genomes in protective coatings prior to their release to the extracellular environment. However, beyond these and perhaps a few other generic attributes, common features among viruses are not so readily apparent. The most compelling conserved traits of viruses will be revealed at the integrated process level, by seeking common patterns in the dynamic networks that direct intracellular resources toward virus growth. Such patterns will be sought in three ways: by formulating and refining in-silico models for the intracellular development of three viruses that represent diverse information-processing strategies: phage T7, human immunodeficiency virus (HIV-1) and vesicular stomatitis virus (VSV); by identifying common characteristics in the intracellular development of these viruses, focusing on the dynamics and efficiencies of information, material and energy flows, and by assessing the feasibility of applying in-silico mutagenesis to generate and characterize the functional diversity within population distributions of viruses, so-called quasi-species. At the level of broader impacts, this is a highly interdisciplinary project that will employ computer simulations to characterize the dynamics and control of cellular resource processing during the development of viruses. The cross-disciplinary experience gained by students and co-workers who pursue this research, as well as the refereed publications, technical presentations and supplements to course lectures that result from this work, will contribute toward the advancement of research and education in biological information processing.

在自然界中，病毒是自我复制的实体，其基因组组成彼此不同（RNA或DNA），它们的基因组大小（跨越两个数量级），以及它们的宿主范围（跨越所有生命王国），但所有病毒都需要表达自己的基因组编码的mRNA功能，使用宿主的翻译机制指导蛋白质合成，复制基因组，并在它们释放到细胞外环境之前将它们产生的后代基因组组装在保护性涂层中。 然而，除了这些和其他一些通用属性之外，病毒之间的共同特征并不那么明显。 通过在动态网络中寻找共同的模式，将细胞内资源导向病毒生长，在整合过程水平上揭示病毒最引人注目的保守特征。 将通过三种方式寻求这种模式：通过制定和完善代表不同信息处理策略的三种病毒的细胞内发育的计算机模型：噬菌体T7，人类免疫缺陷病毒（HIV-1）和水泡性口炎病毒（VSV）;通过识别这些病毒细胞内发育的共同特征，关注信息的动态和效率，物质和能量流，并通过评估应用计算机诱变来产生和表征病毒群体分布（所谓的准种）内的功能多样性的可行性。 在更广泛的影响层面，这是一个高度跨学科的项目，将采用计算机模拟来表征病毒发展过程中细胞资源处理的动态和控制。 从事这项研究的学生和同事所获得的跨学科经验，以及这项工作所产生的参考出版物，技术演示和课程讲座的补充，将有助于推进生物信息处理的研究和教育。