Abstract
Small signalling peptides (SSPs) play crucial roles in plant growth, development, and stress responses. However, accurately identifying and characterising SSPs remains challenging due to their structural diversity and the limitations of current prediction tools. Here, we introduce S2-PepAnalyst, a novel web tool designed to enhance the prediction of SSPs in plants. By integrating comprehensive plant-specific datasets into a machine learning model, S2-PepAnalyst offers versatility, improved accuracy of 99.5% on average, and reliability with a low rate of false negatives compared to existing tools. S2-PepAnalyst provides essential resources for plant biologists and facilitates new discoveries in plant peptide signalling.
Competing Interest Statement
The authors have declared no competing interest.