Abstract：
The nearest-neighbor (NN) model is a general tool for the evaluation for oligonucleotide thermodynamic stability. It is primarily used for the prediction of melting temperatures but has also found use in RNA secondary structure prediction and theoretical models of hybridization kinetics. One of the key problems is to obtain the NN parameters from melting temperatures, and VarGibbs was designed to obtain those parameters directly from melting temperatures. Here we will describe the basic workflow from RNA melting temperatures to NN parameters with the use of VarGibbs. We start by a brief revision of the basic concepts of RNA hybridization and of the NN model and then show how to prepare the data files, run the parameter optimization, and interpret the results.
摘要：
最近邻（NN）模型是评估寡核苷酸热力学稳定性的通用工具。它主要用于预测解链温度，但也可用于RNA二级结构预测和杂交动力学的理论模型。关键问题之一是从熔化温度获得NN参数，和VarGibbs被设计成直接从熔化温度获得这些参数。在这里，我们将描述使用VarGibbs从RNA解链温度到NN参数的基本工作流程。我们首先简要修订了RNA杂交和NN模型的基本概念，然后展示了如何准备数据文件，运行参数优化，并解释结果。
