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Functional Phylogenies

功能系统发育

基本信息

批准号：
EP/H046917/1
负责人：
Nick Jones
金额：
$ 3.5万
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2010
资助国家：
英国
起止时间：
2010 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FH046917%2F1
关键词：
Functional Phylogenies

项目摘要

We now regularly use the genetic sequences of different creatures to make guesses about their common ancestors. A creature's genetic sequence is a long string of symbols. But how can we discuss common ancestors if, instead of knowing strings of symbols about each creature, we only have information about their shapes? Though this is a particularly difficult situation, it is very common. Many objects in the world around us evolve and change their shape but do not have a genetic sequence. For example, the shapes of consumer items, from toothbrushes to cars, are under continual shape evolution but no-one supposes they have genomes. The challenge of making inferences about the past evolution of shapes, and of making guesses about which shapes have recent ancestors in common, is well established. The standard approach to this challenge is to extract sets of numbers that describe the shapes of interest and to use these summary sets to make guesses about the past. This proposal takes a different approach. We aim to develop mathematical techniques that use the shapes themselves, rather than summaries of them, to make inferences about the past. This approach has some advantages: it uses more of the information that we have; it allows us to characterize the process that yields shape evolution; and it allows us to make guesses about the shapes of unseen ancestors (rather than guesses about a restricted set of their features).This proposal aims to advance the study of shape evolution by considering the evolution of mathematical functions. A functional phylogeny is akin to a genetic evolutionary tree where it is a mathematical function, rather than a genetic sequence, that changes through time. We will test our theory by: using computer generated data; performing `Spatial Chinese Whispers' experiments; and investigating how the pronunciation of words has evolved in Romance languages. Our `Spatial Chinese Whispers' experiments will involve the task of drawing curves, one after the other, so that small errors in copying yield a slow drift in curve shape. Our investigation of speech sound evolution first converts the sounds of modern speakers into shapes and then exploits the fact that we are confident about the evolutionary tree of Romance languages. Just as information about current genetic sequences allow us to make guesses about the sequences of past organisms, this approach might allow us to test hypotheses about the sounds of languages we can no longer hear.This work has relevance to those interested in designing shapes for the future, as well as those interested in past shapes. By understanding past shape evolution one can use this to generate reasonable shape transformations which might help in product design. This work aims to take sets of shapes and to make guesses about which is most related to which: this can be very useful in areas which have nothing to do with shape evolution. The ability to detect unusual or familiar shapes has relevance to numerous public and commercial challenges from spotting unusual vehicles to guessing the shapes of letters.

我们现在经常使用不同生物的基因序列来猜测它们共同的祖先。生物的基因序列是一长串符号。但是，如果我们不知道每种生物的符号串，而只知道它们的形状，我们怎么能讨论共同的祖先呢？虽然这是一个特别困难的情况，但它是非常普遍的。我们周围世界的许多物体都在进化并改变它们的形状，但它们并没有基因序列。例如，从牙刷到汽车等消费品的形状都在不断进化，但没有人认为它们有基因组。对形状的过去进化做出推断，以及对哪些形状有共同的最近祖先做出猜测，这是一个挑战。应对这一挑战的标准方法是提取描述感兴趣形状的数字集，并使用这些汇总集来猜测过去。这项建议采取了不同的做法。我们的目标是开发数学技术，使用形状本身，而不是它们的摘要，对过去做出推断。这种方法有一些优点：它使用了更多的信息，我们有;它允许我们描述的过程，产生形状的演变;它允许我们猜测的形状看不见的祖先（而不是猜测一组限制的功能）。功能性基因组类似于基因进化树，它是一个数学函数，而不是一个随时间变化的基因序列。我们将测试我们的理论：使用计算机生成的数据;执行“空间中国耳语”实验;和调查如何发音的话已经在罗马语言的演变。我们的“空间中国耳语”实验将涉及绘制曲线的任务，一个接一个，这样复制中的小错误就会产生曲线形状的缓慢漂移。我们对语音进化的研究首先将现代说话者的声音转换成形状，然后利用我们对罗曼语进化树有信心的事实。正如当前基因序列的信息可以让我们猜测过去生物的序列一样，这种方法可以让我们测试关于我们不再能听到的语言声音的假设。这项工作对那些对设计未来形状感兴趣的人以及对过去形状感兴趣的人都有意义。通过了解过去的形状演变，可以使用它来生成合理的形状转换，这可能有助于产品设计。这项工作的目的是采取一组形状，并猜测哪个与哪个最相关：这在与形状进化无关的领域非常有用。检测不寻常或熟悉形状的能力与许多公共和商业挑战有关，从发现不寻常的车辆到猜测字母的形状。