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Qualitative Modeling of RNA Structure

机译:RNA结构的定性建模

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Determining the folding structure of an RNA molecule from its underlying linear sequence is a complex problem involving both spatial reasoning and the use of knowledge of chemistry and biology. Most research in qualitative physics has traditionally focused on certain types of processes only, and does not provide a method for properly modeling folding. This paper introduces a new AI method for reasoning about the folding process. We present a discrete model for predicting a folding structure and for qualitatively simulating the process of the structure formation over time. We use a simple and approximate model for the task, but accuracy in the prediction is achieved by capturing knowledge from several sources. The model has been implemented in a working program and has been successfully tested on several types of RNAs, including RNAs whose structures have not been fully determined yet.
机译:从其下面的线性序列确定RNA分子的折叠结构是涉及空间推理和化学和生物学知识的复杂问题。在定性物理学中的大多数研究传统上仅关注某些类型的过程,并且不提供适当建模折叠的方法。本文介绍了一种新的AI方法,用于推理折叠过程。我们介绍了一种用于预测折叠结构的离散模型,并在时间上模拟结构形成的过程。我们使用一个简单且近似的模型来完成任务,但通过捕获来自几个来源的知识来实现​​预测的准确性。该模型已在工作计划中实现,并已成功测试了几种类型的RNA,包括尚未完全确定其结构的RNA。

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