Proteasomal cleavage prediction: state-of-the-art and future directions
Ingo Ziegler, Bolei Ma, Bernd Bischl, Emilio Dorigatti, Benjamin Schubert
This paper reviews proteasomal cleavage prediction methods, benchmarks deep learning architectures, and finds that dataset quality limits performance more than model choice.
bioRxiv · Jul 17, 2023 · PreprintBioinformatics