Sujun Li

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O-glycosylation is one of the most important, frequent and complex post-translational modifications. This modification can activate and affect protein functions. Here, we present three support vector machines models based on physical properties, 0/1 system, and the system combining the above two features. The prediction accuracies of the three models have(More)
Protein SUMO modification is an important post-translational modification and the optimization of prediction methods remains a challenge. Here, by using Support Vector Machines algorithm (SVM), a novel computational method was developed for SUMO modification site prediction based on Sequential Forward Selection (SFS) of hundreds of amino acid properties,(More)
We estimated the reproducibility of tandem mass spectra for the widely used collision-induced dissociation (CID) of peptide ions. Using the Pearson correlation coefficient as a measure of spectral similarity, we found that the within-experiment reproducibility of fragment ion intensities is very high (about 0.85). However, across different experiments and(More)
One of the important objectives in mass spectrometry-based proteomics is the identification of post-translationally modified sites in cellular and extracellular proteomes. Proteomics techniques have been particularly effective in studying protein phosphorylation, where tens of thousands of new sites have been recently discovered in all domains of life. Such(More)
In order to find evidence for translation of alternatively spliced transcripts, especially those that result in a change in reading frame, we collected exon-skipping cases previously found by RNA-Seq and applied a computational approach to screen millions of mass spectra. These spectra came from seven human and six mouse tissues, five of which are the same(More)
Metaproteomic studies adopt the common bottom-up proteomics approach to investigate the protein composition and the dynamics of protein expression in microbial communities. When matched metagenomic and/or metatranscriptomic data of the microbial communities are available, metaproteomic data analyses often employ a metagenome-guided approach, in which(More)
Peptide amidination labeling using S-methyl thioacetimidate (SMTA) is investigated in an attempt to increase the number and types of peptides that can be detected in a bottom-up proteomics experiment. This derivatization method affects the basicity of lysine residues and is shown here to significantly impact the idiosyncracies of peptide fragmentation and(More)