Database search post-processing by neural network: Advanced facilities for identification of components in protein mixtures using mass spectrometric peptide mapping.
Database search post-processing by neural network was employed in peptide mapping experiments. The database search was performed using both the known algorithms and score functions, such as Bayesian, MOWSE, Z-score, correlations between calculated and actual peptide length fractional abundance, and, in addition, the probability of protein digest pattern in peptide fingerprint, all embedded in locally developed program. The new signal-processing algorithm based on neural network improves signal-noise separation and is acceptable for automatic protein identification in mixtures. Its power was tested on Helicobacter pylori protein inventory after preceding protein separation by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Increase in protein identification success rate was observed, and about 100 proteins were identified with no need of human participation in database search estimation.
Institute of Biomedical Chemistry, Moscow, Russia. proteomics@ibmh.msk.su
Petr G
PG
Lokhov
Olga V
OV
Tikhonova
Sergei A
SA
Moshkovskii
Eugene I
EI
Goufman
Marina V
MV
Serebriakova
Boris I
BI
Maksimov
Ilya Yu
IY
Toropyguine
Victor G
VG
Zgoda
Vadim M
VM
Govorun
Alexander I
AI
Archakov
D000465:Algorithms; D001499:Bayes Theorem; D002853:Chromatography, Liquid; D019992:Databases as Topic; D015180:Electrophoresis, Gel, Two-Dimensional; D004591:Electrophoresis, Polyacrylamide Gel; D016480:Helicobacter pylori / Q000378:metabolism; D016571:Neural Networks, Computer; D010449:Peptide Mapping / Q000379:methods*; D010455:Peptides / Q000737:chemistry; D011506:Proteins / Q000737:chemistry*; D012984:Software; D021241:Spectrometry, Mass, Electrospray Ionization; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
D010455:Peptides; D011506:Proteins