Design and Implementation of Probability-Based Scoring Function for Peptide Mass Fingerprinting Protein Identification

Author(s):  
Zhao Song ◽  
Luonan Chen ◽  
Chao Zhang ◽  
Dong Xu
2009 ◽  
Vol 3 (1) ◽  
pp. 59-68 ◽  
Author(s):  
Thammasorn Wimada ◽  
Eadjongdee Korakot ◽  
Hongsthong Apiradee ◽  
Porkaew Kriengkrai ◽  
Cheevadhanarak Supapon

One of the major goals of proteomic research is the identification of proteins, a goal that often requires various software tools and databases. These tools have to be able to handle large amounts of data, such as those generated by PMF (Peptide Mass Fingerprinting), a high throughput technique. A newly sequenced organism, Spirulina platensis, was recently used to generate an in silico database, and thus an in-house tool designed for compatibility with this database and its inputs (PMF) was constructed in the present study. With a probability based scoring function, this tool effectively ranked ambiguous protein identification results by using five criteria: score, number of matched peptides, % coverage, pI and molecular weight. As a result, the protein identification step of Spirulina proteomic studies can be achieved precisely. Moreover, a very useful function of this tool is its capability for batch processing, in which the system can handle proteinidentification searches of a hundred of proteins automatically, from a single user’s input. Therefore, the tool not only gives accurate protein identification results but also saves the user time in processing a large amount of data.


PROTEOMICS ◽  
2002 ◽  
Vol 2 (2) ◽  
pp. 157-163 ◽  
Author(s):  
Julie M. Pratt ◽  
Duncan H. L. Robertson ◽  
Simon J. Gaskell ◽  
Isabel Riba-Garcia ◽  
Simon J. Hubbard ◽  
...  

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