BIOCOMPLEXITY: Bacterial and Computational Experiments to Identify General Principles that Govern the Evolution of Complexity

生物复杂性：细菌和计算实验以确定控制复杂性进化的一般原则

• 批准号: 9981397
• 负责人: Richard Lenski
• 金额: $ 405.01万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-11-01 至 2005-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9981397&HistoricalAwards=false
• 关键词: BIOCOMPLEXITY; Bacterial; Computational; Experiments; Identify

Lenski et al.9981397The principal investigators define biocomplexity as the dynamic web of interactions among genes, organisms, and environments. They will investigate the emergence of biocomplexity and examine its consequences for the performance of living organisms and ecological communities. Parallel experiments will be performed with two very different systems, in order to study general principles. One system employs bacteria, and the other system is digital. The latter consists of special computer programs that self-replicate, mutate, and evolve novel sequences of instructions to solve problems. One set of experiments will monitor the evolution of ecosystem complexity, in which a single progenitor diverges into multiple types that perform distinct functions by exploiting different resources. Follow-up experiments will examine the effects of removing member species on the remainder of the community. Another project will develop the software used for studying digital organisms into an educational tool.This project, which is being supported by the Directorates for Biological Sciences, Computer Information Science and Engineering, Engineering, and by the division of Mathematical Sciences and the MPS Office of Multidisciplinary Activities, will impact several scientific fields, and the findings may provide basic information useful for both environmental and biotechnological applications. For example, ecologists may find principles useful for improving the performance of beneficial organisms in the environment. Computer scientists may discover computational strategies, evolved by real organisms that can be employed in developing more complex software.

Lenski等人9981397主要研究人员将生物复杂性定义为基因，生物和环境之间的相互作用的动态网络。 他们将研究生物复杂性的出现，并研究其对生物和生态社区表现的后果。 为了研究一般原理，将使用两个非常不同的系统进行并行实验。 一个系统采用细菌，另一个系统是数字化的。 后者由特殊的计算机程序组成，这些程序会自我复制，突变和进化以解决问题的新颖序列。 一组实验将监视生态系统复杂性的演变，其中单个祖细胞通过利用不同的资源而分散了多种类型的类型。 后续实验将检查去除成员物种对社区其余部分的影响。 另一个项目将开发用于将数字生物研究成教育工具的软件。该项目得到了生物科学，计算机信息科学和工程，工程，工程学以及数学科学和数学科学和MPS多学科活动办公室的支持，该项目将影响几个科学领域，并将影响几个科学领域，以及对环境和生物学的基本信息的影响。 例如，生态学家可能会发现原则可用于改善环境中有益生物的性能。 计算机科学家可能会发现计算策略，这些计算策略是由可用于开发更复杂软件的真实生物所发展的。