scholarly journals Spectral Counting

2020 ◽  
Author(s):  
Keyword(s):  
Spectral Counting

scholarly journals Improved LC-MS chromatographic alignment increases the accuracy of label-free quantitative proteomics: Comparison of spectral counting versus ion intensity-based proteomic quantification strategies

2017 ◽  
Author(s):  
Daniel H.J. Ng ◽  
Jonathan D. Humphries ◽  
Julian N. Selley ◽  
Stacey Warwood ◽  
David Knight ◽  
...  
Keyword(s):  
Cell Biology ◽  
Low Cost ◽  
Quantitative Description ◽  
Protein Quantification ◽  
Global Changes ◽  
Label Free ◽  
Spectral Counting ◽  
Differential Abundance ◽  
Mass Spectrometers ◽  
Wide Range

AbstractThe ability to provide an unbiased qualitative and quantitative description of the global changes to proteins in a cell or an organism would permit the systems-wide study of complex biological systems. Label-free quantitative shotgun proteomic strategies (including LC-MS ion intensity quantification and spectral counting) are attractive because of their relatively low cost, ease of implementation, and the lack of multiplexing restrictions when comparing multiple samples. Owing to improvements in the resolution and sensitivity of mass spectrometers, and the availability of analytical software packages, protein quantification by LC-MS ion intensity has increased in popularity. Here, we have addressed the importance of chromatographic alignment on protein quantification, and then assessed how spectral counting compares to ion intensity-based proteomic quantification. Using a spiked-in protein strategy, we analysed two situations that commonly arise in the application of proteomics to cell biology: (i) samples with a small number of proteins of differential abundance in a larger non-changing background, and (ii) samples with a larger number of proteins of differential abundance. To perform these assessments on biologically relevant samples, we used isolated integrin adhesion complexes (IACs). Technical replicate analysis of isolated IACs resulted in a range of alignment scores using the Progenesis QI software package and demonstrated that higher LC-MS chromatographic alignment scores increased the precision of protein quantification. Furthermore, implementation of a simple sample batch-running strategy enabled good chromatographic alignment for hundreds of samples over multiple batches. Finally, we applied the sample batch-running strategy and compared quantification by LC-MS ion intensity to spectral counting and found that quantification by LC-MS ion intensity was more accurate and precise. In summary, these results demonstrate that chromatographic alignment is important for precise and accurate protein quantification based on LC-MS ion intensity and accordingly we present a simple sample re-ordering strategy to facilitate improved alignment. These findings are not only relevant to label-free quantification using Progenesis QI but may be useful to the wide range of MS-based quantification strategies that rely on chromatographic alignment.

scholarly journals The Oscillation Numbers and the Abramov Method of Spectral Counting for Linear Hamiltonian Systems

2021 ◽  
Vol 248 ◽  
pp. 01002
Author(s):  
Julia Elyseeva
Keyword(s):  
Boundary Conditions ◽  
Hamiltonian Systems ◽  
Spectral Parameter ◽  
Dirichlet Boundary ◽  
Dirichlet Boundary Conditions ◽  
Spectral Counting ◽  
Hamiltonian Problems ◽  
Differential Systems ◽  
Linear Hamiltonian Systems ◽  
Strict Normality

In this paper we consider linear Hamiltonian differential systems which depend in general nonlinearly on the spectral parameter and with Dirichlet boundary conditions. For the Hamiltonian problems we do not assume any controllability and strict normality assumptions which guarantee that the classical eigenvalues of the problems are isolated. We also omit the Legendre condition for their Hamiltonians. We show that the Abramov method of spectral counting can be modified for the more general case of finite eigenvalues of the Hamiltonian problems and then the constructive ideas of the Abramov method can be used for stable calculations of the oscillation numbers and finite eigenvalues of the Hamiltonian problems.

scholarly journals Identifying differences in protein expression levels by spectral counting and feature selection

2008 ◽  
Vol 7 (2) ◽  
pp. 342-356 ◽  
Author(s):  
P.C. Carvalho ◽  
J. Hewel ◽  
V.C. Barbosa ◽  
J.R. Yates III
Keyword(s):  
Feature Selection ◽  
Protein Expression ◽  
Spectral Counting ◽  
Expression Levels
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