CAREER: Modeling made easy: Extending systems biology modeling approaches to genetics and ecology

职业:建模变得简单:将系统生物学建模方法扩展到遗传学和生态学

基本信息

  • 批准号:
    1149123
  • 负责人:
  • 金额:
    $ 106.03万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2012
  • 资助国家:
    美国
  • 起止时间:
    2012-06-01 至 2020-12-31
  • 项目状态:
    已结题

项目摘要

The University of Wisconsin-Madison is awarded a CAREER grant to support Laurence Lowe in his research to extend rigorous mathematical simulation methods and make them available in a user-friendly model description language designed to solve computationally challenging forward simulation problems in biology. Many user-friendly simulation tools have been developed in systems biology, but their underlying mathematical representation impairs their use for important problems in genetics and ecology. This project will transform quantitative modeling into a mainstream activity that will be an integral part of biological research in the future. The first task will be to implement a new language that makes it easy to read and write such models for humans and for computers. To harness the large-scale computing power needed for analyzing complicated models, a link will be built to the evolution@home public global computing system and to private Condor pools. To efficiently store the results produced, a new standard for storing and sharing simulation results will be pioneered. The second goal will be to address combinatorial explosions in genetics and ecology models with algorithms and representations that work efficiently with both systems biology and genetics simulations, and that also allow for distributions of event times other than the standard assumption (exponential). Finally, the project will apply these new tools to intensely studied biological systems, including growth of VSV viruses in cells and adaptive evolutionary ecology of copepods (important zooplankton food source for fish). Close collaborations with neighboring labs will help shape the development of tools to ensure the resulting cyber-infrastructure is useful for cutting edge research. Such research is pivotal for increasing the quantitative rigor, realism and accuracy represented in models that will become increasingly important for various decision support systems.The same language and simulation tools developed for research will be used to teach graduate and undergraduate students, and design innovative teaching materials that improve the understanding of quantitative modeling for diverse audiences. Using "the real thing" is fascinating and transformational for learning, as witnessed by the rise of "R" in statistics. Working with K12 teachers, materials will be developed that explain the importance of good models to a broad audience. To this end, a brief interactive course with comprehension tests will be implemented to impart basic modeling knowledge, encourage responsible use of models, and discourage abuse. Successful completion of the course will provide a "License for Using Models". This and other teaching tools will be developed and tested on K12 students and evolution@home participants. The latter contribute CPU power to simulations of evolution and have a natural interest in models they are simulating, an interest to be met by an engaging website. The overall vision is to raise awareness for the importance of good quantitative models. The PI's career is to build such models. Further information about this project will be available at the PI's lab page at http://evolutionary-research.net/people/loewe.
威斯康星大学麦迪逊分校获得了一项职业补助金,以支持劳伦斯·洛(Laurence Lowe)的研究,以扩展严格的数学模拟方法,并使其以用户友好的模型描述语言可用,旨在解决生物学中计算上具有挑战性的正向模拟问题。系统生物学领域已经开发了许多用户友好的模拟工具,但它们的基础数学表示削弱了它们在遗传学和生态学中重要问题上的应用。该项目将把定量建模转变为主流活动,成为未来生物学研究不可或缺的一部分。第一个任务是实现一种新的语言,使人类和计算机可以轻松地读取和编写此类模型。为了利用分析复杂模型所需的大规模计算能力,将建立一个与evolution@home公共全球计算系统和私有Condor池的链接。为了有效地存储产生的结果,将开创存储和共享模拟结果的新标准。第二个目标是通过与系统生物学和遗传学模拟有效配合的算法和表示来解决遗传学和生态模型中的组合爆炸,并且还允许除标准假设(指数)之外的事件时间分布。最后,该项目将把这些新工具应用于深入研究的生物系统,包括VSV病毒在细胞中的生长和桡足类(鱼类重要的浮游动物食物来源)的适应性进化生态学。与邻近实验室的密切合作将有助于开发工具,以确保最终的网络基础设施对前沿研究有用。此类研究对于提高模型中的定量严谨性、真实性和准确性至关重要,这对于各种决策支持系统将变得越来越重要。为研究开发的相同语言和模拟工具将用于教授研究生和本科生,并设计创新的教材,以提高不同受众对定量建模的理解。使用“真实的东西”对于学习来说是令人着迷且具有变革性的,统计学中“R”的兴起就证明了这一点。我们将与 K12 教师合作开发材料,向广大受众解释良好模型的重要性。为此,将实施带有理解测试的简短互动课程,以传授基本的建模知识,鼓励负责任地使用模型并阻止滥用。成功完成课程将获得“模型使用许可证”。该工具和其他教学工具将在 K12 学生和 evolution@home 参与者中进行开​​发和测试。后者为进化模拟贡献 CPU 能力,并对他们正在模拟的模型有着天然的兴趣,而吸引人的网站可以满足这种兴趣。总体愿景是提高人们对良好定量模型重要性的认识。 PI 的职业就是建立这样的模型。有关该项目的更多信息,请访问 PI 的实验室页面:http://evolutionary-research.net/people/loewe。

项目成果

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Laurence Loewe其他文献

Evolution@home: Global computing quantifies evolution due to Muller's ratchet
  • DOI:
    10.1186/1471-2105-6-s3-p18
  • 发表时间:
    2005-09-21
  • 期刊:
  • 影响因子:
    3.300
  • 作者:
    Laurence Loewe
  • 通讯作者:
    Laurence Loewe
Global Computing for Bioinformatics
生物信息学全球计算
  • DOI:
    10.1093/bib/3.4.377
  • 发表时间:
    2002
  • 期刊:
  • 影响因子:
    9.5
  • 作者:
    Laurence Loewe
  • 通讯作者:
    Laurence Loewe
Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA
使用 Bio-PEPA 量化 SBGN-PD 图中的隐式流程抽象
  • DOI:
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Laurence Loewe;Stuart L. Moodie;Jane Hillston
  • 通讯作者:
    Jane Hillston
Computational models in systems biology
  • DOI:
    10.1186/gb-2008-9-12-328
  • 发表时间:
    2008-01-01
  • 期刊:
  • 影响因子:
    9.400
  • 作者:
    Laurence Loewe;Jane Hillston
  • 通讯作者:
    Jane Hillston

Laurence Loewe的其他文献

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