Abstract
In this paper, we present PRIME-BSPre, a template-based genome-wide method for predicting protein-RNA binding sites that incorporates the RNA sequence and secondary structure as well as the tertiary structure of corresponding RBPs. We are pioneers in introducing low Shannon entropy algorithm in PRIME-BSPre to describe the binding preferences of RBPs on RNA motifs. The LS-PEAK derived from LS-Scores in PRIME-BSPre is utilized to optimize the alignments screening. PRIME-BSPre has been successfully benchmarked on the human genome, demonstrating its excellent prediction performance on independent RBP datasets and its robustness across different cell lines. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-026-12657-3.