A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples.
BACKGROUND: Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable m...
| Main Authors: | , , , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
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2010
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| _version_ | 1797056513943011328 |
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| author | Mantini, D Petrucci, F Pieragostino, D Del Boccio, P Sacchetta, P Candiano, G Ghiggeri, G Lugaresi, A Federici, G Di Ilio, C Urbani, A |
| author_facet | Mantini, D Petrucci, F Pieragostino, D Del Boccio, P Sacchetta, P Candiano, G Ghiggeri, G Lugaresi, A Federici, G Di Ilio, C Urbani, A |
| author_sort | Mantini, D |
| collection | OXFORD |
| description | BACKGROUND: Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data. RESULTS: MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. CONCLUSIONS: The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf. |
| first_indexed | 2024-03-06T19:23:44Z |
| format | Journal article |
| id | oxford-uuid:1b027fed-dd9c-48f4-a8ef-d6ba885ad167 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T19:23:44Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:1b027fed-dd9c-48f4-a8ef-d6ba885ad1672022-03-26T10:57:55ZA computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:1b027fed-dd9c-48f4-a8ef-d6ba885ad167EnglishSymplectic Elements at Oxford2010Mantini, DPetrucci, FPieragostino, DDel Boccio, PSacchetta, PCandiano, GGhiggeri, GLugaresi, AFederici, GDi Ilio, CUrbani, A BACKGROUND: Mass spectrometry (MS) is becoming the gold standard for biomarker discovery. Several MS-based bioinformatics methods have been proposed for this application, but the divergence of the findings by different research groups on the same MS data suggests that the definition of a reliable method has not been achieved yet. In this work, we propose an integrated software platform, MASCAP, intended for comparative biomarker detection from MALDI-TOF MS data. RESULTS: MASCAP integrates denoising and feature extraction algorithms, which have already shown to provide consistent peaks across mass spectra; furthermore, it relies on statistical analysis and graphical tools to compare the results between groups. The effectiveness in mass spectrum processing is demonstrated using MALDI-TOF data, as well as SELDI-TOF data. The usefulness in detecting potential protein biomarkers is shown comparing MALDI-TOF mass spectra collected from serum and plasma samples belonging to the same clinical population. CONCLUSIONS: The analysis approach implemented in MASCAP may simplify biomarker detection, by assisting the recognition of proteomic expression signatures of the disease. A MATLAB implementation of the software and the data used for its validation are available at http://www.unich.it/proteomica/bioinf. |
| spellingShingle | Mantini, D Petrucci, F Pieragostino, D Del Boccio, P Sacchetta, P Candiano, G Ghiggeri, G Lugaresi, A Federici, G Di Ilio, C Urbani, A A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title | A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title_full | A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title_fullStr | A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title_full_unstemmed | A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title_short | A computational platform for MALDI-TOF mass spectrometry data: application to serum and plasma samples. |
| title_sort | computational platform for maldi tof mass spectrometry data application to serum and plasma samples |
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