生命语言的范畴成分分布模型
A Categorical Compositional Distributional Modelling for the Language of Life
摘要：
范畴成分分布模型（DiscoCat）是一种用于自然语言句子意义构成的强大数学模型。由于我们可以将生物序列视为“生命语言”，因此它试图将DisCoCat模型应用于生命语言，看看我们是否可以获得新的见解并更好地理解后者。在这项工作中，我们朝着这个方向迈出了第一步。特别地，我们选择关注蛋白质，因为与其他大分子如DNA或RNA相比，蛋白质的语言特征是最突出的。具体地说，我们把每个蛋白质看作一个句子，把它的组成域看作单词。一个词或句子的意义就是它的生物学功能，蛋白质中结构域的排列与句法相对应。将所有这些放入DisCoCat框架中，我们可以根据蛋白质结构域的功能以及将它们组合在一起的语法规则来“计算”蛋白质的功能。由于蛋白质及其结构域的功能在向量空间中表示，我们提供了一种新的方法来形式化的蛋白质的功能表示。
英文摘要：
The Categorical Compositional Distributional (DisCoCat) Model is a powerful mathematical model for composing the meaning of sentences in natural languages. Since we can think of biological sequences as the "language of life", it is attempting to apply the DisCoCat model on the language of life to see if we can obtain new insights and a better understanding of the latter. In this work, we took an initial step towards that direction. In particular, we choose to focus on proteins as the linguistic features of protein are the most prominent as compared with other macromolecules such as DNA or RNA. Concretely, we treat each protein as a sentence and its constituent domains as words. The meaning of a word or the sentence is just its biological function, and the arrangement of domains in a protein corresponds to the syntax. Putting all those into the DisCoCat framework, we can "compute" the function of a protein based on the functions of its domains with the grammar rules that combine them together. Since the functions of both the protein and its domains are represented in vector spaces, we provide a novel way to formalize the functional representation of proteins.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
