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 abbreviaton ‘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.
Basic Information
| Repository | https://github.com/MorillaLab/s2-PEPANALYST |
| Documentation | https://github.com/MorillaLab/s2-PEPANALYST/tree/main |
| Seminar | Ian Morilla (IHSM-CSIC-UMA) presenta GeoTop, TaelCore, CoMM-BIP y S2-PepAnalyst |
| Main publication (DOI) | 10.1101/2024.08.02.606319 |
| Contact email | ian.morilla@ihsm.uma-csic.es |
| Authors/Maintainers | Ian Morilla |
| Type of application | Jupyter notebook |
| Programming languages | Python |
| Keywords | Omics, Computational Methods, Resources, Data Analysis, Artificial Intelligence, Machine Learning in Biology, Bioinformatics Software and Tools, Data Visualization, Applications of Computational Biology, Computational Techniques, High-performance Computing, Parallel Computing, Web-service, Proteomics, Plant genomics, Deep Learning in Biology, Cloud Computing |
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| Citations (last 12 months) | <100 (~0 as of 15/10/2026) |
| Citations (since first release) | <100 (0 as of 15/10/2026) |
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