NSF-Simons Center for Mathematical and Statistical Analysis of Biology

NSF-西蒙斯生物学数学和统计分析中心

• 批准号: 1764269
• 负责人: Andrew Murray
• 金额: $ 500万
• 依托单位: Harvard 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: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1764269&HistoricalAwards=false
• 关键词: NSF; Simons; Center; Mathematical; Statistical

The NSF-Simons Center for Mathematical and Statistical Analysis of Biology at Harvard University aims to use mathematics and statistics to understand biology well enough for scientists to make accurate predictions of how organisms, from simple bacteria and yeasts to mammals, respond to changes in their genes and their environments. The Center's research will focus on three areas: how cells and organisms make decisions that change their behavior and their fate; how sophisticated structures, from the outer coating of viruses and the machinery that segregates a cell's chromosomes to the structure of embryos and organs, can assemble without explicit instructions; and how organisms change their structures and activities to deal with changes in their environments over timescales that range from minutes to millennia. In each of these areas, the Center will bring together mathematicians and biologists, with the hope that the mathematicians will help to create deeper and more general understanding of biological systems and that the biologists will stimulate the mathematicians to develop new techniques in mathematics, statistics, and computation that can be applied to questions outside as well as inside biology. These close interactions will produce a new generation of scientists who see themselves as both mathematicians and biologists and are thus equipped to tackle a variety of questions that cannot be answered today. The NSF-Simons Center for Mathematical and Statistical Analysis of Biological Systems has three aims -- advancing knowledge of complex biological systems using mathematical and computational tools, developing new mathematics and statistics, and training a new generation of researchers in mathematical and computational biology. The goals of the Center are to ask how molecular networks within individual cells allow them to make developmental decisions, to discover how proteins and cells self-assemble and self-organize to produce intra-cellular structures, tissues, and organs, and to understand how these biological systems adapt within and beyond the lifespan of individual organisms. These questions span a broad range of timescales (from milliseconds to millions of years) and length scales (from microns to meters). To extract general principles, the Center will study a range of experimental systems that span viruses, cells, tissues, organs, and organoids. The Center aims to build predictive and causal mathematical models for decision making, self-organized morphogenesis, and adaptation, linking development and evolution. Just as physics has been intricately allied with mathematics for centuries, biology will be similarly allied with mathematics going forward. The Center aims to strengthen this link by training graduate students and postdocs who are already experts in mathematics and computation to use their skills to provide a layered understanding of biological complexity and by hosting visitors and workshops that will establish broad linkages between mathematicians and biologists who embrace the natural complementarity of these disciplines.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.

哈佛大学的NSF-西蒙斯生物学数学和统计分析中心旨在利用数学和统计学来充分理解生物学，以便科学家能够准确预测生物体（从简单的细菌和酵母到哺乳动物）如何应对基因和环境的变化。该中心的研究将集中在三个领域：细胞和生物体如何做出改变其行为和命运的决定;复杂的结构，从病毒的外壳和分离细胞染色体的机器到胚胎和器官的结构，如何在没有明确指示的情况下组装;以及生物如何改变其结构和活动，以应对从几分钟到几千年的时间尺度上的环境变化。在每一个领域，该中心将汇集数学家和生物学家，希望数学家将有助于创造更深层次和更普遍的理解生物系统和生物学家将刺激数学家开发新的技术，在数学，统计和计算，可以应用于内外生物学的问题。这些密切的互动将产生新一代的科学家，他们认为自己既是数学家又是生物学家，因此有能力解决今天无法回答的各种问题。NSF-西蒙斯生物系统数学和统计分析中心有三个目标-使用数学和计算工具推进复杂生物系统的知识，开发新的数学和统计学，并培养新一代数学和计算生物学研究人员。该中心的目标是询问单个细胞内的分子网络如何使它们能够做出发育决定，发现蛋白质和细胞如何自组装和自组织以产生细胞内结构，组织和器官，并了解这些生物系统如何在个体生物体的寿命内和寿命外适应。这些问题跨越了广泛的时间尺度（从毫秒到数百万年）和长度尺度（从微米到米）。 为了提取一般原理，该中心将研究一系列实验系统，涵盖病毒、细胞、组织、器官和类器官。该中心旨在建立预测和因果数学模型，用于决策，自组织形态发生和适应，将发展和进化联系起来。就像物理学与数学在几个世纪以来一直错综复杂地联系在一起一样，生物学也将与数学紧密联系在一起。该中心旨在通过培训已经是数学和计算专家的研究生和博士后来加强这种联系，利用他们的技能来提供对生物复杂性的分层理解，并通过举办访问者和研讨会来建立数学家和生物学家之间的广泛联系，这些学科具有自然的互补性。通过使用基金会的知识价值和更广泛的影响审查标准进行评估。

项目成果

Computational analysis of size, shape and structure of insect wings

• DOI: 10.1242/bio.040774
• 发表时间: 2019-10-01
• 期刊: BIOLOGY OPEN
• 影响因子: 2.4
• 作者: Salcedo, Mary K.;Hoffmann, Jordan;Mahadevan, L.
• 通讯作者: Mahadevan, L.

The Ribbon-Helix-Helix Domain Protein CdrS Regulates the Tubulin Homolog ftsZ2 To Control Cell Division in Archaea

• DOI: 10.1128/mbio.01007-20
• 发表时间: 2020-07-01
• 期刊: MBIO
• 影响因子: 6.4
• 作者: Darnell, Cynthia L.;Zheng, Jenny;Schmid, Amy K.
• 通讯作者: Schmid, Amy K.

Autocatalytic recombination systems: A reaction network perspective

• DOI: 10.1016/j.mbs.2022.108784
• 发表时间: 2022-02-24
• 期刊: MATHEMATICAL BIOSCIENCES
• 影响因子: 4.3
• 作者: Craciun，Gheorghe;Deshpande，Abhishek;Yu，Polly Y.
• 通讯作者: Yu，Polly Y.

Modulating mesendoderm competence during human germ layer differentiation.

• DOI: 10.1016/j.celrep.2021.109990
• 发表时间: 2021-11-09
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Valcourt JR;Huang RE;Kundu S;Venkatasubramanian D;Kingston RE;Ramanathan S
• 通讯作者: Ramanathan S

Polymerization in the actin ATPase clan regulates hexokinase activity in yeast.

• DOI: 10.1126/science.aay5359
• 发表时间: 2020-02-28
• 期刊: Science (New York, N.Y.)
• 作者: Stoddard PR;Lynch EM;Farrell DP;Dosey AM;DiMaio F;Williams TA;Kollman JM;Murray AW;Garner EC
• 通讯作者: Garner EC