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Eugene I Goufman

Publications and source records attributed to Eugene I Goufman.

2 recordsLinked to original sources
PubMed2005

Ovarian cancer marker of 11.7 kDa detected by proteomics is a serum amyloid A1.

In this study, to reduce the number of major plasma components, we examined thermostable plasma fractions to search for a biomarker of ovarian cancer. An apparent cancer biomarker of 11.7 kDa was detected in these fractions using ProteinChip SELDI-TOF mass spectrometry system. This peak invariably appeared with another close peak of about 11.5 kDa, suggesting that it is a derivative of a larger mass molecule. Of 27 cancer plasma specimens, 15 (55.6%) demonstrated this peak pair, whereas only 2 of 34 controls specimens (5.8%) were shown to express it with low intensity. Using a method involving cysteine modification by 4-vinylpyridine (4-VP), 2-DE and HPLC, these peaks were identified by mass spectrometry as serum amyloid A1 (11.68 kDa) and its N-terminal arginine-truncated form (11.52 kDa).

Amino Acid Sequence↗
PubMed2004

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.

Algorithms↗