Qualitative Modeling of RNA Structure

초록

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.