Tema Fridman

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Proteomic techniques are fast becoming the main method for qualitative and quantitative determination of the protein content in biological systems. Despite notable advances, efficient and accurate analysis of high throughput proteomic data generated by mass spectrometers remains one of the major stumbling blocks in the protein identification problem. We(More)
We have constructed fully self-consistent models of triaxial galaxies with central density cusps. The triaxial generalizations of Dehnen’s (1993) spherical mass models are presented, which have densities that vary as r near the center and r at large radii. We computed libraries of ∼ 7000 orbits in each of two triaxial models with γ = 1 (“weak cusp”) and γ =(More)
We derive the optimal number of peaks (defined as the minimum number that provides the required efficiency of spectra identification) in the theoretical spectra as a function of (i) the experimental accuracy, sigma, of the measured ratio m/z; (ii) experimental spectrum density; (iii) size of the database; (iv) number of peaks in the theoretical spectra; and(More)
Tandem mass spectrometry (MS/MS) is one of the leading proteomics technologies, applicable to a wide range of experiments involving composition analysis of protein mixtures. Currently only /spl sim/10-20% of MS/MS spectral data lead to the successful peptide identifications, and the rate of false positives remains to be high. We propose probability profile(More)
A novel method is proposed for deciphering experimental tandem mass spectra. A large database of previously resolved peptide spectra was used to determine “neighborhood patterns” for each peak category: Cor N-terminus ions, their dehydrated fragments, etc. The established patterns are applied to assign probabilities for new spectra peaks to fit into these(More)
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