Byunghee Shin
Papers
1
Total Citations
50
H-Index
1
About
Byunghee Shin is a prominent figure in computational proteomics, whose work has significantly advanced the accuracy of peptide identification from mass spectrometry data. His primary research focuses on developing sophisticated bioinformatics methods for processing and refining tandem mass spectrometric (MS/MS) data. Shin’s major contribution is the creation of the Postexperiment Monoisotopic Mass Filtering and Refinement (PE-MMR) technique, a groundbreaking approach that filters MS/MS data and refines precursor masses to achieve highly accurate analyses of large-scale proteomics datasets. This method, detailed in his 2008 paper which has garnered 50 citations, directly addresses the critical challenge of ensuring reliable peptide identification in liquid chromatography-tandem mass spectrometry (LC/MS/MS) experiments. By enhancing data accuracy, Shin’s work has provided the proteomics community with a powerful tool for more confident protein identification, enabling deeper insights into complex biological systems. His research remains influential for students and researchers seeking robust computational solutions for high-throughput proteomic data analysis.
Research Focus
Key Achievements
Top Papers
- 1