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Computational and Statistical Analysis of Protein Mass Spectrometry Data
High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computatio...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3266873/ https://www.ncbi.nlm.nih.gov/pubmed/22291580 http://dx.doi.org/10.1371/journal.pcbi.1002296 |
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author | Noble, William Stafford MacCoss, Michael J. |
author_facet | Noble, William Stafford MacCoss, Michael J. |
author_sort | Noble, William Stafford |
collection | PubMed |
description | High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve. |
format | Online Article Text |
id | pubmed-3266873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32668732012-01-30 Computational and Statistical Analysis of Protein Mass Spectrometry Data Noble, William Stafford MacCoss, Michael J. PLoS Comput Biol Review High-throughput proteomics experiments involving tandem mass spectrometry produce large volumes of complex data that require sophisticated computational analyses. As such, the field offers many challenges for computational biologists. In this article, we briefly introduce some of the core computational and statistical problems in the field and then describe a variety of outstanding problems that readers of PLoS Computational Biology might be able to help solve. Public Library of Science 2012-01-26 /pmc/articles/PMC3266873/ /pubmed/22291580 http://dx.doi.org/10.1371/journal.pcbi.1002296 Text en Noble, MacCoss. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Review Noble, William Stafford MacCoss, Michael J. Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title | Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title_full | Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title_fullStr | Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title_full_unstemmed | Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title_short | Computational and Statistical Analysis of Protein Mass Spectrometry Data |
title_sort | computational and statistical analysis of protein mass spectrometry data |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3266873/ https://www.ncbi.nlm.nih.gov/pubmed/22291580 http://dx.doi.org/10.1371/journal.pcbi.1002296 |
work_keys_str_mv | AT noblewilliamstafford computationalandstatisticalanalysisofproteinmassspectrometrydata AT maccossmichaelj computationalandstatisticalanalysisofproteinmassspectrometrydata |