ArticleBMC bioinformatics2014
Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs.
Article in BMC bioinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data.Scientific reports · 2023Article
- 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
- Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014Review
- 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
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Authors and funding
4 authors.
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Abstract
backgroundTandem mass spectrometry-based database searching is currently the main method for protein identification in shotgun proteomics. The explosive growth of protein and peptide databases, which is a result of genome translations, enzymatic digestions, and post-translational modifications (PTMs), is making computational efficiency in database searching a serious challenge. Profile analysis shows that most search engines spend 50%-90% of their total time on the scoring module, and that the spectrum dot product (SDP) based scoring module is the most widely used. As a general purpose and high performance parallel hardware, graphics processing units (GPUs) are promising platforms for speeding up database searches in the protein identification process.
resultsWe designed and implemented a parallel SDP-based scoring module on GPUs that exploits the efficient use of GPU registers, constant memory and shared memory. Compared with the CPU-based version, we achieved a 30 to 60 times speedup using a single GPU. We also implemented our algorithm on a GPU cluster and achieved an approximately favorable speedup.
conclusionsOur GPU-based SDP algorithm can significantly improve the speed of the scoring module in mass spectrometry-based protein identification. The algorithm can be easily implemented in many database search engines such as X!Tandem, SEQUEST, and pFind. A software tool implementing this algorithm is available at http://www.comp.hkbu.edu.hk/~youli/ProteinByGPU.html.
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