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Using a form of MS called tandem MS, or MSIMS, along with a novel algorithm and proprietary bioinformatics software called Scoring Algorithm for Spectral Analysis, Liebler and his group are able to analyze the mass spectra of peptides to establish their sequences, the positions of any modifications, and, by mapping that information back onto the entire protein sequence, the sites of modification in the protein itself.
NIST researchers had developed a method using matrix-assisted time-of-flight mass spectrometry (MALDI-TOF-MS), along with autocorrelation analysis of the resulting mass spectra, to determine the topological nature of the molecules as a function of molecular mass.
The automated interpretation of experimental data, especially mass spectra, is currently the most active area of research.
Their mass was calculated by APCI mass spectra which are in good agreement with theoretical data.
Direct analysis of microorganisms using MALDI-MS provides a number of advantages, such as rapidity, low detection limits, simplified mass spectra (featuring the signals of predominantly singly charged ions), and tolerance to contaminants.
Using two mathematical methods, linear discriminant analysis (LDA), and principal component analysis (PCA), it distinguishes the mass spectra of diseased blood from those of a healthy sample.
Serum mass spectra from different patient groups can be normalized and compared for differences in key clusters of protein masses after SELDI analysis.
Their mass spectra analysis of the exhaust of idling cars fueled with leaded gasoline revealed trace quantities of 44 unexpected halogenated compounds, most of them containing bromine.
Mass resolution is also enhanced with up to 20,000 resolving power at fastest spectral acquisition rates of up to 40 mass spectra per second, accommodating the latest high-throughput rapid-resolution uHPLC liquid chromatography platforms.
Mass spectra reflect the differences in protein sequence and can therefore be reproducibly linked to a particular protein or fragment.
The SE model features stable mass spectra that achieve high sensitivity and stability values.
Hemoglobins C, D-Punjab, E, and O-Arab can all be positively identified directly from the mass spectra of 30-min digests with trypsin (4).