Methods, algorithms and tools in computational proteomics: A practical point of view
Computational MS‐based proteomics is an emerging field arising from the demand of high throughput analysis in numerous large‐scale experimental proteomics projects. The review provides a broad overview of a number of computational tools available for data analysis of MS‐based proteomics data and giv...
        Saved in:
      
    
          | Published in | Proteomics (Weinheim) Vol. 7; no. 16; pp. 2815 - 2832 | 
|---|---|
| Main Author | |
| Format | Journal Article | 
| Language | English | 
| Published | 
        Weinheim
          WILEY-VCH Verlag
    
        01.08.2007
     WILEY‐VCH Verlag Wiley-VCH  | 
| Subjects | |
| Online Access | Get full text | 
| ISSN | 1615-9853 1615-9861  | 
| DOI | 10.1002/pmic.200700116 | 
Cover
| Summary: | Computational MS‐based proteomics is an emerging field arising from the demand of high throughput analysis in numerous large‐scale experimental proteomics projects. The review provides a broad overview of a number of computational tools available for data analysis of MS‐based proteomics data and gives appropriate literature references to detailed description of algorithms. The review provides, to some extent, discussion of algorithms and methods for peptide and protein identification using MS data, quantitative proteomics, and data storage. The hope is that it will stimulate discussion and further development in computational proteomics. Computational proteomics deserves more scientific attention. There are far fewer computational tools and methods available for proteomics compared to the number of microarray tools, despite the fact that data analysis in proteomics is much more complex than microarray analysis. | 
|---|---|
| Bibliography: | ArticleID:PMIC200700116 Innovation Technology Department of the Bizkaia County ark:/67375/WNG-BV1DX4BB-P The Department of Industry, Tourism and Trade of the Government of the Autonomous Community of the Basque Country istex:F840B5A632C60968BC01D112DFF48AF8E8B899FE ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 ObjectType-Review-3  | 
| ISSN: | 1615-9853 1615-9861  | 
| DOI: | 10.1002/pmic.200700116 |