Shotgun mass spectrometry-based proteomics has emerged as the most powerful approach to comprehensively analyze proteins in a biological sample over the last few years. This technology will play a key role in the predictive, preventive, personalized, and participatory medicine design. Correct peptide identification from a tandem mass spectrum is the crucial step to determine the target protein sequence and […]

  Shotgun mass spectrometry (MS) has emerged as a powerful technology for large-scale proteomic analysis recently. By measuring thousands of peptides in a prepared sample, health researchers can gain insight into the complex disease pathways, which can be used for diagnosis and treatment. A crucial problem in the current MS experiments is that not every peptide can be effectively […]

Proteins play crucial roles in almost every biological process. The function of a protein depends on the specific spatial shape that a protein takes in nature. The Protein Structure Prediction problem is to predict the tertiary structure of a protein from its amino acid sequence. Experimental methods (NMR spectroscopy and X-ray crystallography) are slow and […]

The research project aims to develop an effective method that utilizes multiple features to improve mass spectrometry based peptide identification with database search approach. The project is a continuation to the student’s previous research on precursor charge state prediction, since predicted charge state is a novel feature and has a great potential to discriminate the […]

As a result of recent advances in high-throughput technologies, rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, […]

As a result of recent advances in high-throughput technologies, rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, […]