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Related Concept Videos

Proteomics01:33

Proteomics

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A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Detecting differential protein expression in large-scale population proteomics.

So Young Ryu1, Wei-Jun Qian2, David G Camp2

  • 1Stanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA Stanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA, Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, WA 99352, USA and Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA.

Bioinformatics (Oxford, England)
|June 15, 2014
PubMed
Summary

This study introduces Significance Analysis for Large-scale Proteomics Studies (SALPS), a bioinformatics method to address missing peptide quantification in clinical proteomics. SALPS improves biomarker discovery by robustly handling data challenges in large-scale studies.

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Area of Science:

  • Biochemistry
  • Bioinformatics
  • Clinical Proteomics

Background:

  • High-throughput quantitative proteomics using mass spectrometry (MS) is valuable for clinical biomarker discovery.
  • Analyzing quantitative proteomics data presents challenges, including missing peptide quantification, especially for low-abundance peptides.
  • Variations in sample quality and instrument performance across experiments lead to differing numbers of quantified peptides and increased missing values.

Purpose of the Study:

  • To develop bioinformatics methods that effectively handle missing peptide intensity values in large-scale clinical proteomics.
  • To improve the detection of biomarker proteins by addressing data complexities inherent in clinical studies.

Main Methods:

  • Development of a novel bioinformatics approach named Significance Analysis for Large-scale Proteomics Studies (SALPS).
  • SALPS is designed to specifically address missing peptide intensity values arising from experimental variability.
  • The method's performance is evaluated using both simulated data and real-world proteomics data from a large clinical study.

Main Results:

  • The proposed SALPS model demonstrates robust performance in analyzing simulated and clinical proteomics data.
  • The method effectively handles missing peptide intensity values, a common issue in large-scale quantitative proteomics.
  • SALPS provides a reliable approach for analyzing complex clinical proteomics datasets.

Conclusions:

  • SALPS offers a valuable tool for analyzing large-scale clinical proteomics data, particularly in biomarker discovery studies.
  • The method's ability to manage missing data enhances the reliability and scope of proteomic analyses.
  • This approach is expected to be beneficial for clinical studies conducted over extended periods, accommodating inherent data variations.