Lei Li

SBP-SITA is a sequence-based tool for predicting S-itaconation sites, achieving an AUC of 0.73 using an ensemble classifier.

The paper introduces the experiment-split method to address overfitting in cross-validation by splitting data based on experimental sources, using DeepKme as an example to demonstrate its effectiveness.

The paper introduces DeepKhib, a deep-learning framework for predicting lysine 2-hydroxyisobutyrylation sites, showing improved performance over existing methods across multiple species.

MMS2plot is an R package that visualizes MS/MS spectra for modified and non-modified peptides to aid in PTM assignment.