Comparison of Search Engine Contributions in Protein Mass Fingerprinting for Protein Identification
2007
Joo, W.A. (Korea University, Seoul, Republic of Korea) | Lee, J.B. (Korea University, Seoul, Republic of Korea) | Park, M.R. (Eulji University, Daejeon, Republic of Korea) | Lee, J.W. (Korea University, Seoul, Republic of Korea) | Kim, H.J. (Korea University, Seoul, Republic of Korea) | Kim, C.W. (Korea University, Seoul, Republic of Korea), E-mail: [email protected]
Peptide mass fingerprinting (PMF) is a valuable method for rapid and high-throughput protein identification using the proteomics approach. Automated search engines, such as Ms-Fit, Mascot, ProFound, and Peptldent, have facilitated protein identification through PMF. The potential to obtain a true MS protein identification result depends on the choice of algorithm as well as experimental factors that influence the information content in MS data. When mass spectral data are incomplete and/or have low mass accuracy, the "number of matches" approach may be inadequate for a useful identification.
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