CAREER: Reducing barriers for comparative methods

职业：减少比较方法的障碍

• 批准号: 1453424
• 负责人: Brian O'Meara
• 金额: $ 73.83万
• 依托单位: University of Tennessee Knoxville
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-15 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1453424&HistoricalAwards=false
• 关键词: CAREER; Reducing; barriers; comparative; methods

A major question in evolutionary biology is how and why species have changed over time. From observing species in the present, for example, we know that competition can drive species to become different. Rather than remaining two species with similar sizes, those competing species can change, with one becoming larger or smaller than the other. Similar processes of change likely occurred in the past. There are other questions about past processes: how did the extinction of non-avian dinosaurs affect mammal evolution, how have human diseases evolved as humans settled more in cities, and so forth. Evolutionary biologists address these questions by writing a model to describe the process and then estimating aspects of the model: how strongly do species repel each other, what was the rate increase in mammals, how has virulence changed through time. However, for many of these questions, developing the models has been intractable, leaving these questions largely unanswerable. This project will develop tools to make creating these models much easier. It does so by using computers to simulate evolution under a particular model and tries adjusting the model parameters to best predict observed data, an approach known as approximate Bayesian computation. This will be enhanced by hackathons, intense meetings where scientists and developers gather to create or extend software, and which also serve to increase the programming skills and tools of biologists. An additional outcome of this project is the creation of an open course to teach cutting edge methods for understanding the past using family trees of current and extinct species.This project combines new approaches for approximate Bayesian computation (ABC) for comparative methods as a way to implement new models with meetings to have new and experienced coders work together on projects (hackathons) as well as a new open phylogenetics course. The ABC approach will be written in R, given R's widespread usage in the comparative methods user community, and uses a discrete time model that allows biologists to code a model for movement in one generation and then uses this model on a phylogenetic tree. Prototype code is already available (package TreEvo) and will be developed under an open source model. Together, the research and teaching will speed up methods development, broaden the pool (in number and diversity) of people who can create new approaches to answer their questions, and strengthen phylogenetic training in general.

进化生物学中的一个主要问题是物种如何以及为什么随着时间的推移而变化。例如，通过观察现在的物种，我们知道竞争可以驱使物种变得不同。而不是保持两个物种具有相似的大小，这些竞争物种可以改变，其中一个变得比另一个更大或更小。类似的变化过程可能在过去发生过。关于过去的过程还有其他问题：非鸟类恐龙的灭绝如何影响哺乳动物的进化，人类疾病如何随着人类在城市定居而进化等等。进化生物学家通过编写一个模型来描述这个过程，然后估计模型的各个方面来解决这些问题：物种之间相互排斥的程度如何，哺乳动物的速度增加了多少，毒力如何随着时间的推移而变化。然而，对于其中许多问题，开发模型一直很棘手，使这些问题在很大程度上无法回答。该项目将开发工具，使创建这些模型更容易。它通过使用计算机来模拟特定模型下的进化，并尝试调整模型参数以最好地预测观察到的数据，这种方法被称为近似贝叶斯计算。这将通过黑客马拉松来增强，黑客马拉松是科学家和开发人员聚集在一起创建或扩展软件的紧张会议，也有助于提高生物学家的编程技能和工具。该项目的另一个成果是创建一个开放课程，教授使用当前和灭绝物种的家谱来了解过去的尖端方法。该项目结合了比较方法的近似贝叶斯计算（ABC）的新方法，作为一种实现新模型的方法，通过会议让新的和经验丰富的程序员一起工作在项目（黑客马拉松）以及新的开放系统发育学课程上。ABC方法将用R编写，因为R在比较方法用户社区中广泛使用，并使用离散时间模型，允许生物学家在一代人中编码运动模型，然后在系统发育树上使用该模型。原型代码已经可用（包TreEvo），并将在开放源代码模式下开发。总之，研究和教学将加快方法的发展，扩大谁可以创建新的方法来回答他们的问题，并加强一般系统发育训练的人的池（在数量和多样性）。