Conference: SICB 2024: Computational and Physical Models in Research and Teaching to Explore Form-Function Relationships

该会议奖支持参加综合与比较生物学学会(SICB)2024年1月年会上关于将计算和物理模型纳入生物学研究和教学的研讨会和相关研讨会的参与者。随着更广泛的计算能力的普及，以及大学校园内“创客空间”的快速扩张和建设，为生物学家提供了提供独特机会来增进对生物形式和功能关系的理解的数学、物理和工程建模工具。然而，物理模型和计算模型方法在生物科学中的广泛采用往往因为难以形成适当的跨学科合作以及生物学学生技术培训方面的差距而受阻。该奖项支持一个跨学科研讨会，它将促进生物学家、物理学家和工程师之间的讨论和思考，并将加速新的跨学科合作的形成。研讨会突出了早期职业研究人员和科学界代表性不足群体的成员。研讨会的成果包括一次合作讲习班和一篇合成论文，该论文将确定应用物理模型和计算建模来革新生物学知识的创新方法和优先事项，以及创建一个纳入生物学课程的框架。生物系统的紧急行为是多个复杂和相互关联的系统精确协调的结果，使得快速的信号处理和适当的效应器输出成为可能。通过将传统的生物学实验与物理或计算建模相结合，可以实现对这些过程的机械理解。应用这些工具的激活障碍可能很高，特别是对于那些新接触建模的实验室。同样，教育未来的科学家在他们自己的研究和教学中永久使用建模方法也是当务之急。该奖项支持一个跨学科研讨会，该研讨会将促进生物学家、物理学家和工程师之间的讨论和思考，包括职业生涯早期的科学家、国际研究人员和科学界代表性不足的团体的成员，并将加速形成新的研究和教育合作。通过展示跨学科研究和教学方法的潜力，研讨会和研讨会将激励科学家在自己的工作中实施模型，并确定这样做的途径。研讨会报告摘要将发表在SICB期刊《综合与比较生物学》上。该问题将包括一份共同撰写的前瞻性观点论文，回顾该领域的状况，并强调将继续推动生物学知识发现的极限和这些工具的跨学科整合的研究优先事项。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This conference award supports participants in a symposium and associated workshop on incorporating computational and physical models in biological research and teaching at the annual meeting of the Society for Integrative and Comparative Biology (SICB) in January 2024. With greater universal access to computational power as well as the rapid expansion and construction of “maker spaces” across college campuses, mathematical, physical, and engineering modeling tools that offer unique opportunities to advance understanding of organismal form and function relationships are readily available to biologists. However, broad adoption of physical models and computational modeling approaches in the biological sciences is often thwarted by the difficulty of forming appropriate transdisciplinary collaborations as well as gaps in technical training of biology students. This award supports a transdisciplinary symposium that will catalyze discussions and ideation among biologists, physicists, and engineers, and will accelerate the formation of new transdisciplinary collaborations. The symposium highlights early-career researchers and members of groups under-represented in the sciences. Outcomes of the symposium include a collaborative workshop and synthetic paper that will identify innovative approaches and priorities for applying physical models and computational modeling to revolutionize biological knowledge, as well as creating a framework for integration into biology curricula. Emergent behaviors of a biological system are the result of the precise coordination of multiple complex and interconnected systems, enabling rapid signal processing followed by appropriate effector output. A mechanistic understanding of these processes can be achieved by integrating traditional biology experiments with physical or computational modeling. The activation barrier for applying these tools can be high especially for those labs new to modeling. Likewise, it is imperative to educate future scientists to perpetuate the use of modeling approaches in their own research and teaching. The award supports a transdisciplinary symposium that will catalyze discussions and ideation among biologists, physicists, and engineers, including early-career scientists, international researchers, and members of groups under-represented in the sciences, and will accelerate the formation of new research and education collaborations. By showcasing the potential of cross-disciplinary research and teaching approaches, the symposium and workshop will inspire scientists to implement models in their own work and identify pathways for doing so. Summaries of the symposium presentations will be published in the SICB journal, Integrative and Comparative Biology. That issue will include a jointly-authored, forward-looking perspective paper reviewing the state of the field and highlighting research priorities that will continue pushing the limits of biological knowledge discovery and transdisciplinary integration of these tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.