NSF-Simons Center for Quantitative Biology

NSF-西蒙斯定量生物学中心

• 批准号: 1764421
• 负责人: Richard Carthew
• 金额: $ 500万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1764421&HistoricalAwards=false
• 关键词: NSF; Simons; Center; Quantitative; Biology

The NSF-Simons Center for Quantitative Biology at Northwestern University will catalyze quantitative approaches to fundamental questions about growth and development by integrating mathematical modeling and analysis with state-of-the-art experimental investigations. One of the great mysteries of our world is how myriad forms of life grow and develop from a single cell into a new organism. The sequence of developmental events is surprisingly robust, even though the biological processes emerge from a complex interplay between genetic programming and environmental inputs that can be quite variable. The revolution in "omics" and high-throughput analysis has uncovered associations in this process, but the causal mechanisms remain unknown. The research at the Center seeks to understand the underlying biological mechanisms and principles associated with these remarkable phenomena. The Center focuses on four interrelated research areas selected to elucidate distinct aspects of growth and development. Each project integrates hypothesis-driven mathematical modeling and data-driven mathematical analysis with advanced imaging, genomics, and metabolomics tools to explore biological processes across time, space, and extrinsic variables. Graduate, undergraduate, and postdoctoral trainees will be embedded in shared mathematical and biological environments, engaged in work with investigators across this multi-disciplinary spectrum. The Center will build interdisciplinary capacity through a visiting scholars program, a named fellows program, a pilot project program, a middle-school science club learning module, workshops, and training courses. It will advance knowledge in the biological and mathematical sciences, generate new conceptual models explaining development and growth, and train new investigators who are experienced in both fields.The NSF-Simons Center for Quantitative Biology aims to transform understanding of organismal growth and development through quantitative approaches that combine three fundamental mathematical areas: dynamical systems theory, stochastic processes, and dimension reduction. The Center also intends to make substantial technical advances in quantitative approaches, by producing new high-dimensional biological datasets across spatial (cellular to organismal) and temporal scales, new conceptual models of diverse developmental processes, and mathematical models that describe developmental emergence. Project 1 will produce single-cell RNA-sequence data from a frog embryo and mouse embryonic stem cells at various stages during development and new conceptual models of embryogenesis using dynamical systems theory and statistical dimension reduction. The high-dimensional approach and datasets from Project 2 will enable a new mathematical model of roundworm growth as a function of genotype and environmental variables. Project 3 will provide a new overarching conceptual model of environmentally-driven oscillatory dynamics in the fruit fly and unique datasets that link molecular signatures in the fat body of the fly with phenotypic behavior. The image analysis of Project 4 will study stochastic variation in fruit fly development and generate a new mathematical model of the impact of protein expression noise on development processes. Across projects, new statistical methodologies and methods for combining multiple types of mathematical approaches will be tested and validated. New biological datasets, conceptual models, and mathematical models will be made available to the broader research community. The Center will promote interdisciplinary education and workforce training at the intersection of mathematical sciences and biology, scientific outreach to the underserved K-12 education community, and interdisciplinary training for visiting scholars.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.

西北大学的NSF-西蒙斯定量生物学中心将通过将数学建模和分析与最先进的实验研究相结合，促进有关生长和发育的基本问题的定量方法。 我们这个世界最大的谜团之一就是无数的生命形式是如何从一个细胞成长和发展成一个新的有机体的。 发育事件的顺序是惊人的强大，即使生物过程出现从一个复杂的相互作用之间的遗传编程和环境的投入，可以是相当可变的。 “组学”和高通量分析的革命已经揭示了这一过程中的关联，但因果机制仍然未知。 该中心的研究旨在了解与这些显着现象相关的潜在生物学机制和原理。 该中心侧重于四个相互关联的研究领域，以阐明增长和发展的不同方面。 每个项目都将假设驱动的数学建模和数据驱动的数学分析与先进的成像，基因组学和代谢组学工具相结合，以探索跨时间，空间和外在变量的生物过程。 研究生，本科生和博士后学员将被嵌入共享的数学和生物学环境中，与这个多学科领域的研究人员一起工作。 该中心将通过访问学者计划，命名研究员计划，试点项目计划，中学科学俱乐部学习模块，研讨会和培训课程来建立跨学科能力。 它将推进生物学和数学科学的知识，产生新的概念模型解释发展和增长，并培养新的研究人员谁是在这两个领域的经验。NSF-西蒙斯中心定量生物学旨在通过量化的方法，结合联合收割机三个基本的数学领域：动力系统理论，随机过程和降维改造生物体的生长和发展的理解。 该中心还打算在定量方法方面取得实质性的技术进步，通过在空间（细胞到生物体）和时间尺度上产生新的高维生物数据集，不同发育过程的新概念模型，以及描述发育出现的数学模型。 项目1将利用动态系统理论和统计降维技术，从青蛙胚胎和小鼠胚胎干细胞发育过程中的各个阶段获得单细胞RNA序列数据，并建立胚胎发生的新概念模型。 项目2的高维方法和数据集将使蛔虫生长的新数学模型成为基因型和环境变量的函数。 项目3将提供果蝇中环境驱动的振荡动力学的新的总体概念模型，以及将果蝇脂肪体中的分子特征与表型行为联系起来的独特数据集。 项目4的图像分析将研究果蝇发育中的随机变化，并生成蛋白质表达噪声对发育过程影响的新数学模型。 在各个项目中，将测试和验证新的统计方法和结合多种数学方法的方法。 新的生物数据集，概念模型和数学模型将提供给更广泛的研究界。 该中心将促进数学科学和生物学交叉领域的跨学科教育和劳动力培训，为服务不足的K-12教育社区提供科学服务，并为访问学者提供跨学科培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Characterization of larval growth in C. elegans cuticle mutants.

• DOI: 10.17912/micropub.biology.000662
• 发表时间: 2022
• 期刊: microPublication biology
• 作者: Nyaanga, Joy;Shirman, Sasha;Mangan, Niall M;Andersen, Erik C
• 通讯作者: Andersen, Erik C

Linkage mapping reveals loci that underlie differences in C. elegans growth

连锁图谱揭示了秀丽隐杆线虫生长差异背后的基因座

• DOI: 10.1101/2022.04.25.489412
• 发表时间: 2022
• 期刊: bioRxiv
• 作者: Nyaanga, Joy;Andersen, Erik C.
• 通讯作者: Andersen, Erik C.

Src acts with WNT/FGFRL signaling to pattern the planarian anteroposterior axis

• DOI: 10.1242/dev.200125
• 发表时间: 2022-04-01
• 期刊: DEVELOPMENT
• 影响因子: 4.6
• 作者: Bonar, Nicolle A.;Gittin, David, I;Petersen, Christian P.
• 通讯作者: Petersen, Christian P.

Temporal dynamics of faculty hiring in mathematics

数学教师招聘的时间动态

• DOI: 10.1057/s41599-023-01708-9
• 发表时间: 2023
• 期刊: Humanities and Social Sciences Communications
• 作者: FitzGerald, Cody;Huang, Yitong;Leisman, Katelyn Plaisier;Topaz, Chad M.
• 通讯作者: Topaz, Chad M.

Topological data analysis of zebrafish patterns

• DOI: 10.1073/pnas.1917763117
• 发表时间: 2020-03-10
• 期刊: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
• 影响因子: 11.1
• 作者: McGuirl, Melissa R.;Volkening, Alexandria;Sandstede, Bjorn
• 通讯作者: Sandstede, Bjorn