Design and implementation of probability-based scoring function for peptide mass fingerprinting protein identification.
Protein identification through high-throughput mass spectrum data is an important domain in proteomics. Peptide mass fingerprinting (PMF) is one of the major methods for protein identification using the mass-spec technology. We developed a software package called "ProteinDecision" for PMF protein identification, together with a user-friendly graphical interface. "ProteinDecision" can handle the issues of selecting peaks from mass spectrum, transforming database format, displaying the top ranks of identification result, and detailed information for each ranking. We used a novel scoring function by considering the distribution of matching a mass-to-charge and peak intensity in a database based on the MOWSE table. Our new scoring function is assessed better than existing ones by comparing the computational results using experimental PMF data. A standalone version of "ProteinDecision" is freely available upon request.
Song
Zhao
Z
Comput. Sci. Dept., Missouri Univ., Columbia, MO 65211-2060, USA.
Chen
Luonan
L
Zhang
Chao
C
Xu
Dong
D
D000465:Algorithms; D000595:Amino Acid Sequence; D019295:Computational Biology / Q000379:methods*; D003201:Computers; D030562:Databases, Protein; D013058:Mass Spectrometry / Q000379:methods; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010449:Peptide Mapping / Q000295:instrumentation* / Q000379:methods; D010455:Peptides / Q000737:chemistry; D011336:Probability; D011506:Proteins / Q000737:chemistry*; D040901:Proteomics / Q000295:instrumentation* / Q000379:methods; D012984:Software
D010455:Peptides; D011506:Proteins