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High-throughput proteomics: a methodological mini-review.

Miao Cui1,2, Chao Cheng3,4,5, Lanjing Zhang6,7,8,9

  • 1Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Laboratory Investigation; a Journal of Technical Methods and Pathology
|August 3, 2022
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Summary
This summary is machine-generated.

High-throughput proteomics methods are advancing biomedical research and clinical practice. These powerful tools aid in understanding disease mechanisms and developing precision medicine and drug discovery.

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Area of Science:

  • Biomedical research
  • Proteomics
  • Genomics

Background:

  • Proteomics is crucial in the post-genomic era for addressing complex biomedical challenges.
  • Rapid advancements in proteomic technologies and computational models have occurred in the last decade.
  • High-throughput proteomics offers new avenues for understanding biological systems.

Purpose of the Study:

  • To summarize existing and emerging high-throughput proteomics approaches.
  • To discuss computational and statistical methods for proteomic data analysis.
  • To provide guidance on the utilization of modern proteomics tools.

Main Methods:

  • Mass spectrometry
  • Protein pathway array
  • Next-generation tissue microarrays
  • Single-cell proteomics
  • Single-molecule proteomics
  • Luminex
  • Simoa
  • Olink Proteomics

Main Results:

  • High-throughput proteomics enables a deeper understanding of disease pathogenesis.
  • These methods facilitate the identification of disease-specific signaling networks.
  • Computational and statistical algorithms enhance proteomic data mining, integrating multi-omics data.

Conclusions:

  • Advances in high-throughput proteomics are transforming basic research and clinical applications.
  • Modern proteomics holds significant potential for prognostic oncology and precision medicine.
  • The field is pivotal for accelerating drug discovery and development.