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MCtandem: an efficient tool for large-scale peptide identification on many integrated core (MIC) architecture
Chuang Li1,2, Kenli Li3,4, Keqin Li1,5,6
1College of Computer Science and Electronic Engineering, Hunan University, Lushannan Road, Changsha, 410082, China.
MCtandem accelerates peptide identification in shotgun proteomics using a novel parallel algorithm on Intel Many Integrated Core architecture. This open-source tool significantly enhances processing speed and scalability for large-scale MS/MS spectra datasets.
Area of Science:
- Computational proteomics
- Bioinformatics
- High-performance computing
Background:
- Tandem mass spectrometry (MS/MS) database searching is standard for peptide identification.
- Current methods struggle with the increasing volume and complexity of proteomics data.
- Efficient algorithms are needed for large-scale MS/MS spectra dataset processing.
Purpose of the Study:
- To present MCtandem, an efficient tool for large-scale peptide identification.
- To leverage Intel Many Integrated Core (MIC) architecture for big data processing.
- To improve the speed and scalability of computational proteomics.
Main Methods:
- Developed MCtandem, featuring a novel parallel match scoring algorithm (MIC-SDP) with two-level parallelization.
- Implemented optimization strategies including pre-fetching, communication overlapping, multithreading, and hyper-threading.
- Utilized Intel MIC architecture for enhanced computational performance.
Main Results:
- Achieved a 28-fold speedup on a single MIC compared to the original CPU implementation.
- Demonstrated superior scalability over MapReduce-based programs (MR-Tandem) on an MIC cluster.
- MCtandem processes large MS/MS spectra datasets efficiently.
Conclusions:
- MCtandem offers a significant advancement in computational proteomics for large-scale data analysis.
- The tool provides a viable solution for accelerating peptide identification.
- MCtandem is an open-source C++ software available for public use and modification.
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