1 code implementation • 24 Oct 2022 • Ingo Ziegler, Bolei Ma, Ercong Nie, Bernd Bischl, David Rügamer, Benjamin Schubert, Emilio Dorigatti
While direct identification of proteasomal cleavage \emph{in vitro} is cumbersome and low throughput, it is possible to implicitly infer cleavage events from the termini of MHC-presented epitopes, which can be detected in large amounts thanks to recent advances in high-throughput MHC ligandomics.
1 code implementation • 14 Sep 2022 • Emilio Dorigatti, Bernd Bischl, Benjamin Schubert
Accurate in silico modeling of the antigen processing pathway is crucial to enable personalized epitope vaccine design for cancer.
no code implementations • 31 Jan 2022 • Emilio Dorigatti, Jann Goschenhofer, Benjamin Schubert, Mina Rezaei, Bernd Bischl
In this work, we thus propose to tackle the issues of imbalanced datasets and model calibration in a PUL setting through an uncertainty-aware pseudo-labeling procedure (PUUPL): by boosting the signal from the minority class, pseudo-labeling expands the labeled dataset with new samples from the unlabeled set, while explicit uncertainty quantification prevents the emergence of harmful confirmation bias leading to increased predictive performance.