MSDaPl - Molecular & Cellular Proteomics

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27. Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., Harris, M. A., Hill, D. P., Issel-Tarver, L., Kasarskis, A., Lewis, S., Matese, J. C., Richardson, J. E., Ringwald, M., Rubin, G. M., and Sherlock, G. (2000) Nat Genet 25, 25-29 28. Zhang, B., Chambers, M. C., and Tabb, D. L. (2007) J Proteome Res 6, 3549-3557 20
FIGURE LEGENDS: Figure 1. Where MSDaPl fits into the broad proteomics workflow. MSDaPl is not intended to be a workflow manager, but a platform for archiving, interpreting, and disseminating the data generated by each step of the proteomics workflow. Figure 2. An overview of the different databases and programs that support MSDaPl. Arrowheads in the diagram indicate the flow of information, database icons represent the separate databases, and the gears indicate the support programs responsible for processing and inserting data into the databases. Data from all databases are viewable in the web interface, and two support programs are responsible for processing FASTA sequence database files and the proteomics data files. All results may be exported in a format suitable for insertion into public databases. Figure 3: A diagram illustrating how core tables in the msData database schema may be extended to support data of that type generated by separate programs. In this example, the table responsible for storing a peptide search result is extended by tables containing columns specific to Mascot, X!Tandem, Sequest, ProLuCID, and BiblioSpec. The connections between the tables indicate exactly one row in the core search result table may have zero or one rows in one of the extension tables. 21
Page 1 and 2: MCP Papers in Press. Published on M
Page 3 and 4: SUMMARY Mass spectrometry-based pro
Page 5 and 6: INTRODUCTION Mass spectrometry-base
Page 7 and 8: long-term archiving, searching, eva
Page 9 and 10: describe that search result. Adding
Page 11 and 12: PROJECTS DATABASE MSDaPl uses a pro
Page 13 and 14: processed by a “job queue manager
Page 15 and 16: Gene Ontology Analysis: To help app
Page 17 and 18: eported results. To accomplish this
Page 19: REFERENCES 1. Deutsch, E. W. (2010)
Page 23 and 24: Sample Preparation Data Acquisition
Page 25: msRunSearchResult PK id runSearchID

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