The Small-Number Limit of Biological Information Processing

智力价值：各种大小的生物，从单细胞到多细胞生物体，都能处理能量，如光能或化学能，用于生长、发育和修复。他们还处理信息，使自己的行为适应环境中不断变化的环境和不断变化的内部状态。例如，细胞必须调整其特定蛋白质的产生，以应对环境的变化，包括来自附近细胞的信号，以及来自自身DNA的新指令。这些反应相当于“生物计算机”的信息处理，这意味着只要尊重人类设计的计算机和自然产生的生物系统之间的区别，我们就可以利用信息技术和计算机科学的工具来促进我们对复杂生物系统的理解。这项研究解决了三个不同的中心点。与当前的工程系统形成直接对比的是，目前的工程系统被设计为将噪声降至最低，部署了在制造时固定的电路，并依赖于少量相同的子单元(例如，二维芯片上的晶体管)，生物系统似乎：(1)利用噪声为其优势；(2)动态调整其处理方法；以及(3)利用一组异常多样化的潜在机制。在计算机模拟的帮助下，研究人员将推广计算理论中的经典结果，如电路大小的Shannon-Lyupanov界，以解释生物学中已知的限制和差异。此外，它们还将把在大规模实验室研究中不断发现的各种各样的实际处理机制纳入数学框架，例如基因表达的并行表观遗传调节。这样的工作将有助于将过去60年来在计算理论方面所作的巨大投资应用于生物系统的研究。更广泛的影响：预计该项目将产生对广大科学和工程受众有用的成果。预计将为生物系统的“逆向工程”开发的新算法将适用于其他领域；因此，项目资源的一部分专门用于使为提取逻辑结构而开发的技术可供更广泛的社区使用。项目资源还将用于培训和指导新墨西哥州圣达菲学院的本科生和研究生，该学院提供独特的、注重研究的跨学科教育体验。通过该研究所的NSF REU(本科生研究经验)计划和研究生项目的研究人员合作者网络招募的学生将在调查人员的指导下进行研究，并在同行评议的文献中发表他们的结果。最后，调查人员将向在新墨西哥州服务不足的农村地区任教的公立学校教师开展外联活动，并接触到在STEM领域代表不足的少数群体的大量学生。外展活动将与NSF GUTS(成长科学思维)项目负责人艾琳·李合作进行。在新墨西哥州索科罗的Guts Summer师范学院，PI将向初中和高中教师介绍生物系统中信息处理的概念，并与他们合作开发方法，将这些内容纳入教学计划、头脑风暴活动和科学课堂上使用的游戏。调查人员还将在李的指导下，为参与新墨西哥州超级计算挑战计划的中学生提供指导和指导。

Intellectual Merit: Living entities of all sizes, from single cells to multi-cellular organisms, process energy, such as light or chemical energy, for use in growth, development and repair. They also process information, adapting their behavior to changing circumstances in their environment and to changing internal states. For example, a cell must adjust its production of specific proteins in response to changes in its environment, including signals from nearby cells, as well as new instructions from its own DNA. These responses amount to information processing by "biological computers," which suggests that we can advance our understanding of complex biological systems using the tools of information technology and computer science, as long as the distinctions between human-designed computers and naturally-occurring biological systems are respected. This research addresses three central points of difference. In direct contrast to current engineered systems, which are designed to minimize noise, are deployed with circuitry fixed at time of fabrication, and rely on a small number of identical subunits (for example, transistors on a two-dimensional chip), biological systems appear to: (1) use noise to their advantage; (2) dynamically adjust their processing methods; and (3) exploit an unusually diverse set of underlying mechanisms. Aided by computer simulations, the investigators will generalize classical results in the theory of computation, such as the Shannon-Lyupanov bounds for circuit size, to account for the constraints and differences known to obtain in biology. In addition they will bring into a mathematical framework the great variety of actual processing mechanisms, such as the parallel epigenetic regulation of gene expression, that are being continuously uncovered in large-scale laboratory investigations. Such work will aid in applying the vast investment made in the theory of computation over the last sixty years to the study of biological systems. Broader Impacts:The project is expected to produce results useful to a wide scientific and engineering audience. It is anticipated that the new algorithms to be developed for the "reverse engineering" of biological systems will be applicable in other domains; therefore, a portion of the project resources is devoted to making techniques developed for the extraction of logical structures available for use by the broader community. Project resources will also be devoted to the training and mentoring of undergraduate and graduate students at the Santa Fe Institute in New Mexico, which provides a unique, research-focused, interdisciplinary educational experience. Students, recruited through the Institute's NSF REU (Research Experiences for Undergraduates) program and through the Investigators' network of collaborators at graduate programs, will conduct research, and publish their results in peer-reviewed literature, under the guidance of the Investigators. Finally, the Investigators will carry out outreach activities to public school teachers who teach in under-served rural areas in New Mexico and reach large numbers of students from minority groups under-represented in STEM fields. The outreach will be conducted in collaboration with Irene Lee, head of the NSF GUTS (Growing Up Thinking Scientifically) program. At the GUTS Summer Teacher Institutes in Socorro, New Mexico, the PI will introduce middle and high school teachers to the concepts of information processing in biological systems and work with them to develop ways to incorporate this content into lesson plans, brainstorming activities and games for use in science classrooms. The Investigators will also, with guidance from Lee, provide mentorship and coaching to secondary students involved in the New Mexico Supercomputing Challenge Program.