aceSPROTify: A protein-centric machine learning framework for small protein identification with validation in cancer proteomics
Small proteins, typically under 100 amino acids in length, constitute an emerging class of functional biomolecules involved in diverse biological processes. Despite their importance, they are frequently overlooked in genome annotation, as conventional prediction tools prioritize canonical-length open reading frames (ORFs) or rely on nucleotide sequences that may not capture the protein-level physicochemical properties governing stability and detectability. To address this, we developed SPROTify, a protein-centri…
A machine learning classifier built on amino acid features predicted small proteins accurately and found 334 candidates in six cancer proteomics cohorts, 36 of them differentially expressed.
The structural modeling only suggests specialized functional roles in tumor biology; the abstract reports computational candidates and does not confirm their function.
Evidence
- Peer-reviewedNew Biotechnology2026-10-13
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Truvace Impact Record TRV-2026-2034, v1: “SPROTify: A protein-centric machine learning framework for small protein identification with validation in cancer proteomics.” Truvace, 2026-10-20. /record/TRV-2026-2034 (accessed at citation time). sha256 56f5d6ea413ce11d…
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