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When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
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The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
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Spin systems where the difference in chemical shifts of the coupled nuclei is greater than ten times J are called first-order spin systems. These nuclei are weakly coupled, and their chemical shifts and coupling constant can generally be estimated from the well-separated signals in the spectrum.
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When magnetic nuclei in a sample achieve resonance and undergo relaxation, the signal detected in NMR is an approximately exponential free induction decay. Fourier transform of an exponential decay yields a Lorentzian peak in the frequency domain. Lorentzian peaks in an NMR spectrum are defined by their amplitude, full width at half maximum, and position, where the peak width is governed by the spin-spin relaxation time alone. In real experiments, however, the applied magnetic field is rendered...
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The role of the detectors in High-Performance Liquid Chromatography (HPLC) is to analyze the solutes as they exit from the chromatographic column. The detector recognizes the solute's property and generates corresponding electrical signals, which are converted into a readable graph of the detector's response versus elution time called a chromatogram at the computer. There are several types of HPLC detectors, each with its own advantages and limitations, depending on the analyte...
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Deep Learning-Based Prediction of Decoy Spectra for False Discovery Rate Estimation in Spectral Library Searching.

Chak Ming Jerry Chan1, Dominik Madej1, Chun Kit Jason Chung1

  • 1Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China 999077.

Journal of Proteome Research
|April 19, 2025
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Summary
This summary is machine-generated.

This study introduces a novel shuffle-and-predict method for generating decoy spectra in proteomic data analysis. This approach enhances false discovery rate estimation for predicted spectral libraries without needing template spectra.

Keywords:
false discovery ratepeptide identificationpredicted decoyshotgun proteomics

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Area of Science:

  • Proteomics
  • Computational Biology
  • Bioinformatics

Background:

  • Predicted spectral libraries offer extensive coverage for proteomic data analysis.
  • Target-decoy search is a standard method for false discovery rate (FDR) estimation in proteomics.
  • Existing decoy generation methods are validated for experimental libraries but not for predicted libraries.

Purpose of the Study:

  • To evaluate the performance of decoy methods in predicted library scenarios.
  • To introduce and assess a new decoy generation approach: shuffle-and-predict.
  • To determine the effectiveness of predicted decoys for FDR estimation.

Main Methods:

  • Exploration of the shuffle-and-predict decoy library generation approach.
  • Generation of decoy spectra without reliance on template spectra.
  • Experimental validation of the proposed decoy method's performance.

Main Results:

  • The shuffle-and-predict method generates diverse decoy spectra without template spectra.
  • Decoy method performance in predicted library scenarios was elucidated.
  • The study demonstrated the quality of predicted decoys for accurate FDR estimation.

Conclusions:

  • The shuffle-and-predict approach is a viable strategy for decoy generation in predicted spectral libraries.
  • This method expands the utility of predicted libraries in proteomic data analysis.
  • The findings support the use of predicted decoys for robust FDR control.