pFind: A Comprehensive Software Platform for Proteomics Data Analysis
10:30-12:00, 19 Nov. 2024
Room 148, E1 Building
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ABSTRACT
The deep analysis of massive mass spectrometry data has long been a critical challenge in the field of proteomics. Traditional mass spectrometry data analysis methods often exhibit low identification rates due to their inability to effectively search for peptides with unexpected digestion patterns and modifications. We developed the pFind 3 method for deep analysis of mass spectrometry data, which expands the search space by five orders of magnitude, enabling effective searches for peptides with any types of digestions, modifications, and amino acid mutations. pFind 3 consistently achieves an identification rate of 70-85% on conventional high-throughput proteomics datasets. Subsequently, we analyzed a draft dataset of the human proteome, resulting in approximately a twofold increase in the number of identified peptides and a significant reduction in the error rate of identification results. Finally, we applied the pFind engine to chemoproteomic data analysis, proposing the pChem data analysis method and software based on a blind database search strategy, which has demonstrated excellent results in characterizing probe modification types and accurately calculating modification masses.
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BIOGRAPHY
Dr. Chi is a Professor at the Institute of Computing Technology, Chinese Academy of Sciences. His academic journey began with a Bachelor of Engineering in Computer Science and Technology from Jilin University. He then pursued his Doctor of Engineering at the Institute of Computing Technology, Chinese Academy of Sciences. After earning his doctorate, Dr. Chi joined the Institute of Computing Technology as an Assistant Professor in July 2013. He advanced to the role of Associate Professor in September 2016, demonstrating his commitment to research and education in computing technology. Currenly, Dr. Chi is a Professor at Chinese Academy of Sciences.
来源：生命科学与生物医学学域
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