Computational, Statistical and AI-driven Proteomics
A software system for high-coverage and high-confidence de novo peptide sequencing via mirror proteases and deep learning
A software tool for prediction of peptide detectabilitues in proteomics using deep learning
A software tool for prediction of peptide digestibilities in proteomics using deep learning
A software tool for prediction of peptide detectabilities in proteomics using random forest algorithm
A software tool for prediction of peptide quantitative factors and unbiased label-free absolute protein quantification
A software tool for localization and quality control of protein modifications detected by both open and close search
A software tool for quality control of single amino acid variations detected by tandem mass spectrometry
A software tool for N-Linked glycopeptide identification based on open mass spectral library search
Multiple Hypothesis Testing and False Discovery Rate Control
An R package for deep neural network-based feature selection with local false discovery rate estimation
An R package for Local false discovery rate estimation with competition-based procedures for variable selection
An R package for null-free false discovery rate control using decoy permutations for multiple hypothesis testing