ArticleJournal of proteome research2012
Tempest: GPU-CPU computing for high-throughput database spectral matching.
Article in Journal of proteome research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
12 citing papers in PubMed.
- GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data.Scientific reports · 2023Article
- Software Options for the Analysis of MS-Proteomic Data.Methods in molecular biology (Clifton, N.J.) · 2021Article
- Extremely Fast and Accurate Open Modification Spectral Library Searching of High-Resolution Mass Spectra Using Feature Hashing and Graphics Processing Units.Journal of proteome research · 2019Article
- Accelerating a cross-correlation score function to search modifications using a single GPU.BMC bioinformatics · 2018Article
- Tempest: Accelerated MS/MS Database Search Software for Heterogeneous Computing Platforms.Current protocols in bioinformatics · 2016Article
- The SEQUEST family tree.Journal of the American Society for Mass Spectrometry · 2015Article
- A deeper look into Comet--implementation and features.Journal of the American Society for Mass Spectrometry · 2015Article
- Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs.BMC bioinformatics · 2014Article
- Next generation distributed computing for cancer research.Cancer informatics · 2014Review
- SILAC surrogates: rescue of quantitative information for orphan analytes in spike-in SILAC experiments.Analytical chemistry · 2013Article
- Current algorithmic solutions for peptide-based proteomics data generation and identification.Current opinion in biotechnology · 2013Review
- Communication-avoiding micro-architecture to compute Xcorr scores for peptide identification.International Conference on Field-programmable Logic and Applications : [proceedings]. International Conference on Field-Programmable Logic and ApplicationsArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Modern mass spectrometers are now capable of producing hundreds of thousands of tandem (MS/MS) spectra per experiment, making the translation of these fragmentation spectra into peptide matches a common bottleneck in proteomics research. When coupled with experimental designs that enrich for post-translational modifications such as phosphorylation and/or include isotopically labeled amino acids for quantification, additional burdens are placed on this computational infrastructure by shotgun sequencing. To address this issue, we have developed a new database searching program that utilizes the massively parallel compute capabilities of a graphical processing unit (GPU) to produce peptide spectral matches in a very high throughput fashion. Our program, named Tempest, combines efficient database digestion and MS/MS spectral indexing on a CPU with fast similarity scoring on a GPU. In our implementation, the entire similarity score, including the generation of full theoretical peptide candidate fragmentation spectra and its comparison to experimental spectra, is conducted on the GPU. Although Tempest uses the classical SEQUEST XCorr score as a primary metric for evaluating similarity for spectra collected at unit resolution, we have developed a new "Accelerated Score" for MS/MS spectra collected at high resolution that is based on a computationally inexpensive dot product but exhibits scoring accuracy similar to that of the classical XCorr. In our experience, Tempest provides compute-cluster level performance in an affordable desktop computer.
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Registered trials
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