Planning Grant: An Engineering Research Center for the Engineering of Emergent Biocomplexity (ERC-EEB)

规划资助：新兴生物复杂性工程研究中心（ERC-EEB）

• 批准号: 1937105
• 负责人: Jonathan Butcher
• 金额: $ 10万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1937105&HistoricalAwards=false
• 关键词: Planning; Grant; Engineering; Research; Center

Engineering Research Center for the Engineering of Emergent Biocomplexity: Draft AbstractPart 1: Persistent societal challenges prohibit broad-based advancement and human flourishing. Cancer and structural heart defects remain prevalent, unpredictable, and destructive to both families and public resources. Habitat challenges limit production of high-value crops like broccoli. Biotechnology employment is oppressively concentrated in a few large cities, restricting economic opportunity and family planning. These diverse grand challenges exhibit complex commonalities that motivate an integrated solution. Specifically, we believe three facets of biocomplexity?developmental, adaptive, and pathological?are governed by as-yet-unknown emergent construction principles or Rules of Life (one of the NSF?s 10 Big Ideas). We propose an Engineering Research Center for the Engineering of Emergent Biocomplexity (EEB). EEB will pursue foundational science, technology enablement, and economic translation of the engineering system of Emergent Biocomplexity. We will identify construction rules that govern emergent biocomplexity by interrogating three engineering test-beds for which we have extensive expertise and established experimental systems: 1) Developmental emergence: heart morphogenesis, 2) Adaptive emergence: inflorescence morphogenesis, and 3) Pathological emergence: Glioblastoma morphogenesis. Multi-scale, systems-level understanding from each test-bed will cross-inform mechanisms in the others, and through convergent research we will achieve transformative engineering outcomes with high impact: 1) A bench-grown robust, structurally advanced ventricle to advance quantitative developmental biology and enable direct evaluation of restorative approaches for malformed hearts. 2) New broccoli amenable to Eastern US climates with consumer-preferred structural architecture and preservation of vital nutrients. 3) An engineered glioblastoma tumor test platform to identify and validate new drug targets based on controlling emergent behaviors inaccessible to current technologies. In the process of achieving these goals, we will innovate next generation quantitative live imaging and multi-scale/multi-valent computational simulation technology that will accelerate and advance the understanding and control of dynamic biological complexity. We will leverage these science and engineering gains with innovative emergence-based STEM training to transform broaden biotechnology related employment access. Tackling this Grand Challenge requires the deep collaboration of many experts across diverse disciplines (e.g. Math, Plant science, Engineering, Epistemology), siloed disciplinary cultures and language barriers, institutional barriers, and geographical distance. Our institutions: Cornell University, City College of New York, University of Pittsburgh, and the Ohio State University, are ideally positioned within key rural and inner-city domains. This planning grant will help coalesce the academic and industrial expertise and collective infrastructure, build lines of community trust, and refine our strategic plan to carry out these goals. Further, this grant will enable us to engage disparate community stakeholders early in the process to improve our unique emergent computational workforce development program.Part 2: We will plan an ERC to pursue a new convergent research field of emergence science and engineering, focused to discover the Rules of Life that are conserved or unique between diverse emergent biological systems. We will apply deep convergence and team science to refine the communication of emergence science across discipline chasms and identify science tools for interrogating variation and robustness within complex biological systems. This will be achieved through cross-collaborative, multi-institutional test bed team meetings whereby the science and engineering frontiers are solidified and well-grounded paths forward with technical and knowledge success milestones are stratified. Through these meetings, we will establish and prioritize shared needs for engineering a new modular multi-valent computational simulation platform and multi-scale quantitative imaging systems. These systems will provide transformative data generation and analysis tools for accelerating the science and engineering of emergent biocomplexity, using each test bed domain to stretch and refine their capabilities. These technology pipelines will additionally serve as engagement nodes for computational biotechnology firms as they seek to expand their footprints into this emerging economic sector. We will engage regional industry leaders through the planning process to further integrate their technology and training desires. Further, our leadership team includes communication and team formation/team performance experts who will study this planning process to develop models for best practices for ideation and team communication within convergent research environments. The success of our planning strategy will establish a compelling cross-platform test case and refine a new process of cross-disciplinary team engagement for transforming science and engineering research for identifying and solving shared highly complex problems. The proposed planning process will also refine stakeholder needs for culturally responsive workforce generation program for a Center-credentialed computational gig-economy. We will work with existing remote workforce talent and their employers to frame training, certification, and advancement ladder ideals for career sustainability and advancement within computational simulation and analysis space. This broad based, branded and securely managed system would eliminate location oppression in the workforce and enable emergent expertise production. This approach will also catalyze rural engagement in STEM education and the economy. We will also coalesce and refine our novel emergence science and engineering concepts through broadly accessible science symposia, from which focused reviews in leading science journals will evangelize the rationale and approaches. These meetings will also help refine how we continue to include diverse voices from across discipline and stakeholder boundaries for sustaining impact through the ERC period. Finally, these components will then be integrated into a formal ERC proposal to implement the research, engineering, and workforce development goals.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.

工程研究中心新兴生物复杂性：抽象草案1：持续的社会挑战禁止基于广泛的进步和人类蓬勃发展。癌症和结构性心脏缺陷仍然普遍存在，对家庭和公共资源的破坏性。栖息地挑战限制了像西兰花等高价值作物的生产。生物技术就业被压迫地集中在一些大城市，限制了经济机会和计划生育。这些多样化的挑战表现出复杂的共同点，激发了综合解决方案。具体来说，我们相信生物复杂性的三个方面？发展，适应性和病理？受到尚未尚未尚未新兴的新兴建筑原则或生命规则（NSF？S 10大思想之一）控制。我们提出了一个新兴生物复杂性工程研究中心（EEB）。 EEB将追求新兴生物复杂性工程系统的基础科学，技术支持和经济翻译。我们将通过询问三个工程测试床，以确定我们具有广泛专业知识和建立的实验系统的构造规则：1）发育出现：心形出现：2）适应性出现：花序形态发生：旋律学：3）病理学：神经胶质细胞瘤形态发生。来自每个测试床的多尺度，系统级别的理解将跨越其他测试机制，通过收敛研究，我们将实现具有很高影响的变革性工程成果：1）长凳成年的坚固，结构上的高级心室以提高定量定量发育生物学并能够直接评估畸形心脏的修复方法。 2）新的西兰花可与美国东部的气候合作，具有消费者偏爱的结构建筑和保存重要养分。 3）一个工程的胶质母细胞瘤肿瘤测试平台，可基于控制当前技术无法访问的紧急行为来识别和验证新药物靶标。在实现这些目标的过程中，我们将创新下一代定量实时成像和多尺度/多价计算模拟技术，这些技术将加速并提高对动态生物学复杂性的理解和控制。我们将利用基于创新的STEM培训来利用这些科学和工程的成就来改变生物技术相关的就业机会。应对这一巨大挑战需要许多专家在不同学科（例如数学，植物科学，工程，认识论），孤立的纪律文化和语言障碍，机构障碍和地理距离的深入合作。我们的机构：康奈尔大学，纽约市城市学院，匹兹堡大学和俄亥俄州立大学，理想地位于主要的农村和市中心领域。该计划赠款将有助于合并学术和工业专业知识和集体基础设施，建立社区信任的界限，并完善我们实现这些目标的战略计划。此外，这项赠款将使我们能够在此过程的早期与不同的社区利益相关者参与，以改善我们独特的新兴计算劳动力发展计划。第2部分：我们将计划一个ERC追求新出现科学和工程的新融合研究领域，以发现发现，以发现发现生命规则在各种新兴生物系统之间是保守或独特的。我们将运用深厚的融合和团队科学来完善跨学科界的出现科学的交流，并确定科学工具，以询问复杂的生物系统内的变化和鲁棒性。这将通过跨企业，多机构的测试床团队会议来实现，在该会议上，科学和工程前沿巩固了良好的路径，并以技术和知识成功的里程碑进行了良好的路径。通过这些会议，我们将建立并优先考虑工程新的模块化多价计算模拟平台和多尺度定量成像系统的共同需求。这些系统将使用每个测试床域来伸展和完善其功能，提供加速新兴生物复杂性的科学和工程的变革性数据生成和分析工具。这些技术管道还将作为计算生物技术公司寻求将足迹扩展到这一新兴经济领域的参与节点。我们将通过计划过程与区域行业领导者联系，以进一步整合他们的技术和培训欲望。此外，我们的领导团队包括沟通和团队组成/团队绩效专家，他们将研究此计划过程，以开发融合研究环境中构想和团队沟通的最佳实践模型。我们的计划策略的成功将建立一个引人注目的跨平台测试案例，并完善跨学科团队参与的新过程，以改造科学和工程研究，以识别和解决共享的高度复杂问题。拟议的计划过程还将提高利益相关者的需求，以实现中心计算的计算演出经济学的文化响应式劳动力生成计划。我们将与现有的远程劳动力人才及其雇主合作，以构建计算模拟和分析领域中职业可持续性和进步的培训，认证和晋升阶梯理想。这种基于广泛的品牌和安全管理的系统将消除劳动力中的位置压迫并实现新兴的专业知识生产。这种方法还将催化农村参与STEM教育和经济。我们还将通过广泛可访问的科学专题讨论会结合并完善我们新颖的出现科学和工程概念，在领先的科学期刊上的重点评论将传播福音的基本原理和方法。这些会议还将有助于完善我们如何继续在整个ERC期间继续涵盖各个学科和利益相关者边界的各种声音。最后，这些组件将被整合到正式的ERC提案中，以实施研究，工程和劳动力发展目标。该奖项反映了NSF的法定任务，并被认为值得通过基金会的知识分子和更广泛的影响评估标准通过评估来获得支持。 。