Pattern recognition receptors (PRRs) play crucial roles in the innate immune system, and are able to identify pathogen-associated molecular patterns and damage-associated molecular patterns. Accurate identification of PRRs is essential for understanding their functions. In the present work, a random forest based method was proposed to identify PRRs, in which the sequences were formulated by using the optimal features. In the 10-fold cross validation test, an accuracy of 80.95% was obtained in identifying PRRs. We wish that the proposed method will become a useful tool, or at least play a complementary role to the existing predictors for identifying PRRs.

模式识别受体（PRR）在先天免疫系统中起关键作用，并且能够识别病原体相关的分子模式和损伤相关的分子模式。准确识别PRR对于了解其功能至关重要。在目前的工作中，提出了一种基于随机森林的方法来识别PRR，其中通过使用最佳特征来制定序列。在10倍交叉验证测试中，鉴定PRR的准确度为80.95％。我们希望所提出的方法将成为有用的工具，或者至少在现有的预测因子识别PRR方面起补充作用。