Natural computatoin with genetic processes

自然计算研究受自然启发的计算模型。该领域的主要目标包括通过研究计算来提高我们对自然过程的理解，设计用于创建计算（如生物计算）的新方法，以及创建算法来分析所展示的特征的数据。我们对DNA编辑领域的生物过程特别感兴趣。 在进化过程中，DNA发生了许多变化，从微小的变化到称为转座因子的大部分，转座因子可以从基因组的一个位置复制/剪切和粘贴到另一个位置。这些较大的片段很重要，因为它们可以通过插入必要的基因而造成伤害，并且被认为是物种形成的主要因素。它们占人类基因组的45%，但它们目前并不活跃。我们将模拟它们的进化运动，并通过检查包括人类在内的不同生物体中发生的模式来预测它们的活动和年龄。我们还将研究它们用于定制计算的能力，因为转座因子因其在基因治疗中的潜力而受到称赞，基因治疗通常会改变生物体的DNA以治疗疾病。使用理论方法，我们将探索更一般类型的生物计算与转座因子。 以前人们认为单个个体的DNA是相对静态的，在生命周期内或同一个体的多个细胞之间不会发生显着变化。一个例外是一种被称为纤毛虫的生物体，它们已知会进行大量的DNA重排，这是它们生存所必需的。但今年，DNA重排已被发现发生在鱼类。事实上，人类在同一个体的不同细胞之间进行DNA编辑已经被发现，并被认为与疾病有关。由于它似乎发生得更广泛，研究纤毛虫的既定模式是有益的。我们有兴趣使用自然计算来理解这些重排，并预测它们如何在生物学上发生。我们正在创建计算模型和模拟来执行此类预测。

Natural computing investigates models of computation inspired by nature. Major objectives of this area include improving our understanding of natural processes by studying computation, devising new methods for creating computation such as biocomputing, and creating algorithms to analyze data from exhibited characteristics. We are especially interested in biological processes in the area of DNA editing. Many changes occur to DNA over the course of evolution, ranging from small changes, to large sections called transposable elements which can copy/cut and paste from one position of a genome to another. These larger segments are important as they can cause harm by inserting themselves into necessary genes, and are thought to be a major factor in speciation. They make up 45% of the human genome, however they are not currently active. We will model their evolutionary movement and predict their activity and age by examining patterns that occur across different organisms including humans. We will also examine their ability to be used for custom computation as transposable elements are being lauded for their potential with gene therapy, which changes the DNA of a living organism, usually to treat disease. Using theoretical methods, we will explore more general types of biocomputation with transposable elements. It had previously been thought that DNA within a single individual was relatively static and did not change significantly within a lifespan or between multiple cells of the same individual. One exception to this is an organism called ciliates which are known to perform large amounts of DNA rearrangements, necessary for their survival. But this year, DNA rearrangements have been found to occur in fish. In fact, human DNA editing between different cells of the same individual has been discovered and is thought to be related to disease. Since it appears to be occurring more broadly, studying the established patterns in ciliates is beneficial. We are interested in understanding these rearrangements using natural computing, and predicting how they could occur biologically. We are creating computational models and simulations to perform such predictions.