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2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments
BACKGROUND: The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological e...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2475538/ https://www.ncbi.nlm.nih.gov/pubmed/18605993 http://dx.doi.org/10.1186/1471-2105-9-302 |
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author | Allmer, Jens Kuhlgert, Sebastian Hippler, Michael |
author_facet | Allmer, Jens Kuhlgert, Sebastian Hippler, Michael |
author_sort | Allmer, Jens |
collection | PubMed |
description | BACKGROUND: The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. RESULTS: In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. CONCLUSION: We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage. |
format | Text |
id | pubmed-2475538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-24755382008-07-19 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments Allmer, Jens Kuhlgert, Sebastian Hippler, Michael BMC Bioinformatics Software BACKGROUND: The amount of information stemming from proteomics experiments involving (multi dimensional) separation techniques, mass spectrometric analysis, and computational analysis is ever-increasing. Data from such an experimental workflow needs to be captured, related and analyzed. Biological experiments within this scope produce heterogenic data ranging from pictures of one or two-dimensional protein maps and spectra recorded by tandem mass spectrometry to text-based identifications made by algorithms which analyze these spectra. Additionally, peptide and corresponding protein information needs to be displayed. RESULTS: In order to handle the large amount of data from computational processing of mass spectrometric experiments, automatic import scripts are available and the necessity for manual input to the database has been minimized. Information is in a generic format which abstracts from specific software tools typically used in such an experimental workflow. The software is therefore capable of storing and cross analysing results from many algorithms. A novel feature and a focus of this database is to facilitate protein identification by using peptides identified from mass spectrometry and link this information directly to respective protein maps. Additionally, our application employs spectral counting for quantitative presentation of the data. All information can be linked to hot spots on images to place the results into an experimental context. A summary of identified proteins, containing all relevant information per hot spot, is automatically generated, usually upon either a change in the underlying protein models or due to newly imported identifications. The supporting information for this report can be accessed in multiple ways using the user interface provided by the application. CONCLUSION: We present a proteomics database which aims to greatly reduce evaluation time of results from mass spectrometric experiments and enhance result quality by allowing consistent data handling. Import functionality, automatic protein detection, and summary creation act together to facilitate data analysis. In addition, supporting information for these findings is readily accessible via the graphical user interface provided. The database schema and the implementation, which can easily be installed on virtually any server, can be downloaded in the form of a compressed file from our project webpage. BioMed Central 2008-07-07 /pmc/articles/PMC2475538/ /pubmed/18605993 http://dx.doi.org/10.1186/1471-2105-9-302 Text en Copyright © 2008 Allmer et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Allmer, Jens Kuhlgert, Sebastian Hippler, Michael 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title | 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title_full | 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title_fullStr | 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title_full_unstemmed | 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title_short | 2DB: a Proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
title_sort | 2db: a proteomics database for storage, analysis, presentation, and retrieval of information from mass spectrometric experiments |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2475538/ https://www.ncbi.nlm.nih.gov/pubmed/18605993 http://dx.doi.org/10.1186/1471-2105-9-302 |
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