Foundational aspects of bioinformation and biocomputation

生物信息和生物计算的基础方面

• 批准号: RGPIN-2017-04626
• 负责人: Kari, Lila
• 金额: $ 3.06万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710756
• 关键词: Foundational; aspects; bioinformation; biocomputation

In the same way we use the letters of the alphabet to write text, and bits 0 and 1 to write computer machine code, the four basic DNA units (A - adenine, C - cytosine, G - guanine, T - thymine) are used by Nature to write genetic information as DNA strands. The possibility of encoding symbolic information on DNA, and the fact that biochemical processes such as cut-and-paste of DNA strands have been proved to be able to perform arithmetic and logic operations, led to the development of the field of DNA computing and molecular programming. Bioinformation and biocomputation are different from their electronic counterparts in several aspects. First, biodata is not associated to a memory location but consists of infinitesimal DNA strands free-floating in solution. Second, in contrast to data in an electronic computer, which is passive, data-encoding DNA strands can interact with each other in programmable ways due to their Watson-Crick complementarity. Third, each data encoding DNA strand is usually present in millions of identical copies, and the bio-operations operate according to statistical laws. I aim to develop and investigate mathematical models of bioinformation and biocomputation that take into account such specific characteristics, as well as explore mathematical properties of naturally occurring DNA sequences, and their applications. To this end, I approach the issue of data encoding on DNA by proposing to develop a formal-language-based "theory of bioinformation and biocomputation". This includes defining and investigating new concepts that capture the biological reality of DNA- and RNA-encoded information, as well as investigating properties of bio-operations, and their relationships to traditional models of information and computation. Besides its potential significance for the design of programmable DNA-based computational devices, the impact of this research is that it creates a mutually enriching link between theoretical computer science and molecular biology. Secondly, I propose an investigation into DNA self-assembly as a computational tool, the results of which could have potential implications for experimental DNA nanocomputations, and for the molecular programming of complex nanostructures. Lastly, I propose to gain insights into the mathematical properties of naturally-occurring bioinformation by investigating the connection between the syntactical structure of genomic sequences and species classification. This includes investigating Chaos Game Representations of DNA sequences as genomic signatures, as well as applications of this method to HIV-1 virus subtyping and to the classification of marine microbial eukaryotes based on their RNA transcriptomes. The potential impact of such an alignment-free universal classification method could be significant, given that 86% of existing species on Earth and 91% of species in the oceans still await classification.

就像我们用字母表中的字母来写文本，用0和1位来写计算机机器代码一样，四个基本的DNA单元（A -腺嘌呤，C -胞嘧啶，G -鸟嘌呤，T -胸腺嘧啶）被自然界用来写遗传信息作为DNA链。在DNA上编码符号信息的可能性，以及DNA链的剪切和粘贴等生物化学过程已被证明能够执行算术和逻辑运算的事实，导致了DNA计算和分子编程领域的发展。 生物信息和生物计算在几个方面不同于电子技术。首先，生物数据不与存储位置相关联，而是由在溶液中自由漂浮的无限小的DNA链组成。第二，与被动的电子计算机中的数据相反，由于沃森-克里克互补性，编码数据的DNA链可以以可编程的方式相互作用。第三，每个编码DNA链的数据通常存在于数百万个相同的拷贝中，并且生物操作根据统计规律进行操作。 我的目标是开发和研究考虑到这些特定特征的生物信息和生物计算的数学模型，以及探索自然发生的DNA序列的数学特性及其应用。 为此，我的做法的DNA上的数据编码的问题，建议开发一个正式的语言为基础的“理论的生物信息和生物计算”。这包括定义和研究捕获DNA和RNA编码信息的生物现实的新概念，以及研究生物操作的特性及其与传统信息和计算模型的关系。除了对基于DNA的可编程计算设备的设计具有潜在意义外，这项研究的影响还在于它在理论计算机科学和分子生物学之间建立了一个相互丰富的联系。其次，我提出了一个调查DNA自组装作为一种计算工具，其结果可能有潜在的影响实验DNA纳米计算，和复杂的纳米结构的分子编程。最后，我建议通过以下方式深入了解自然发生的生物信息的数学特性： 研究基因组序列的句法结构与物种分类之间的联系。这包括调查混沌游戏表示的DNA序列作为基因组签名，以及应用这种方法的HIV-1病毒分型和海洋微生物真核生物的基础上，他们的RNA转录组的分类。鉴于以下情况，这种无障碍通用分类方法的潜在影响可能很大： 地球上86%的现存物种和海洋中91%的物种仍在等待分类。