An overview of DeepLncPro. (A) Data sets. The dataset contains 2339 positive and 2339 negative samples from human and 3077 positive and 3077 negative samples from mouse. Each sample was intercepted at different lengths from 61 bp to 301 bp with a step of 40 bp. (B) Feature encoding. These samples were encoded by using three feature encoding methods. The encoded features were merged into a 13 × L matrix. (C) Framework of DeepLncPro. DeepLncPro was built based on convolutional neural network. Each sample got a prediction score, ranging from 0 to 1. If the score was >0.5, the sequence is predicted as a lncRNA promoter; otherwise, a non-lncRNA promoter.