S2-PepAnalyst
Our web tool, S2-PepAnalyst, is designed to predict SSPs from input sequences or uploaded files (FASTA/FA/TXT) and identify functional similarities across peptide families (e.g., CLE, RALF, PEP). While the abbreviation ‘SSP’ is sometimes used generically for small secreted peptides, this web focuses on peptides with confirmed or predicted signalling functions (i.e., peptide ligands). Unlike conventional approaches that treat signal peptide identification, size filtering, and downstream validation as separate steps, our tool unifies them into a single, optimised pipeline.
Info
Members (researchers): Ian Morilla
Research Groups: Plant-virus interaction, Machine Learning in Multi-Omics (MLiMO)
Contact Email: ian.morilla@ihsm.uma-csic.es
Tool Repository: https://github.com/MorillaLab/s2-PEPANALYST
Documentation: https://github.com/MorillaLab/s2-PEPANALYST/tree/main
Publications DOI: https://doi.org/10.1101/2024.08.02.606319
Artificial Intelligence, Cloud Computing, Data Visualization, Deep Learning in Biology, High-performance Computing, Machine Learning in Biology, Parallel Computing, Plant genomics, Proteomics, Web-service