ArticleJournal of proteome research2009
Low cost, scalable proteomics data analysis using Amazon's cloud computing services and open source search algorithms.
Article in Journal of proteome research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed.
- aws-s3-integrity-check: an open-source bash tool to verify the integrity of a dataset stored on Amazon S3.GigaByte (Hong Kong, China) · 2023Article
- Cloudy with a Chance of Peptides: Accessibility, Scalability, and Reproducibility with Cloud-Hosted Environments.Journal of proteome research · 2021Article
- Cloud Computing Enabled Big Multi-Omics Data Analytics.Bioinformatics and biology insights · 2021Review
- Selective protein enrichment in calcium oxalate stone matrix: a window to pathogenesis?Urolithiasis · 2019Article
- Deep Learning-based MSMS Spectra Reduction in Support of Running Multiple Protein Search Engines on Cloud.Proceedings. IEEE International Conference on Bioinformatics and Biomedicine · 2017Article
- Stone former urine proteome demonstrates a cationic shift in protein distribution compared to normal.Urolithiasis · 2017Article
- TRPC3 channels critically regulate hippocampal excitability and contextual fear memory.Behavioural brain research · 2015Article
- Processing shotgun proteomics data on the Amazon cloud with the trans-proteomic pipeline.Molecular & cellular proteomics : MCP · 2015Article
- Proteomics for systems toxicology.Computational and structural biotechnology journal · 2014Review
- Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics.Physiological genomics · 2014Article
- Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs.BMC bioinformatics · 2014Article
- Bioinformatics on the cloud computing platform Azure.PloS one · 2014Article
- Targeting the endothelial progenitor cell surface proteome to identify novel mechanisms that mediate angiogenic efficacy in a rodent model of vascular disease.Physiological genomics · 2013Article
- ISPTM: an iterative search algorithm for systematic identification of post-translational modifications from complex proteome mixtures.Journal of proteome research · 2013Article
- A novel spectral library workflow to enhance protein identifications.Journal of proteomics · 2013Article
- Method for rapid protein identification in a large database.BioMed research international · 2013Article
- Translational biomedical informatics in the cloud: present and future.BioMed research international · 2013Review
- MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification.Bioinformatics (Oxford, England) · 2011Article
- Biomedical cloud computing with Amazon Web Services.PLoS computational biology · 2011Article
- In silico research in the era of cloud computing.Nature biotechnology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
One of the major difficulties for many laboratories setting up proteomics programs has been obtaining and maintaining the computational infrastructure required for the analysis of the large flow of proteomics data. We describe a system that combines distributed cloud computing and open source software to allow laboratories to set up scalable virtual proteomics analysis clusters without the investment in computational hardware or software licensing fees. Additionally, the pricing structure of distributed computing providers, such as Amazon Web Services, allows laboratories or even individuals to have large-scale computational resources at their disposal at a very low cost per run. We provide detailed step-by-step instructions on how to implement the virtual proteomics analysis clusters as well as a list of current available preconfigured Amazon machine images containing the OMSSA and X!Tandem search algorithms and sequence databases on the Medical College of Wisconsin Proteomics Center Web site ( http://proteomics.mcw.edu/vipdac ).
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.