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Related Concept Videos

Proteomics01:33

Proteomics

9.4K
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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Genomics02:02

Genomics

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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Protein Networks02:26

Protein Networks

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An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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A Streamlined Approach for Mass Spectrometry-Based Proteomics Using Selected Tissue Regions
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Proteomics and Bioinformatics in Biomedical Research.

Thomas Kislinger1, Igor Jurisica2,3

  • 1Program in Proteomics and Bioinformatics, Banting and Best Institute of Medical Research, University of Toronto, ON thomas.kislinger@utoronto.ca.

Cancer Genomics & Proteomics
|August 10, 2019
PubMed
Summary

This review covers mass spectrometry (MS) technologies for proteomics, enabling high-confidence protein detection. It also summarizes sample separation, bioinformatics tools, and medical proteomics advances in cancer, heart, and diabetes research.

Keywords:
Proteomicsbioinformaticscancer biologydiabetesheart diseasemass spectrometryreview

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Area of Science:

  • Biochemistry
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Proteomics, the large-scale study of proteins, has advanced significantly with mass spectrometry (MS).
  • Current MS technologies allow for the detection of hundreds to thousands of proteins with high confidence in single experiments.
  • Analyzing complex biological samples requires sophisticated separation and data analysis strategies.

Purpose of the Study:

  • To summarize basic mass spectrometry (MS) technologies used in proteomics.
  • To provide an overview of sample separation strategies and bioinformatics tools for managing proteomics data.
  • To review recent advances in medical proteomics, specifically in cancer, cardiovascular, and diabetes research.

Main Methods:

  • Summary of fundamental mass spectrometry (MS) techniques for protein identification.
  • Overview of chromatographic and electrophoretic separation methods.
  • Discussion of bioinformatics pipelines for large-scale proteomics data analysis.

Main Results:

  • Detailed explanation of current MS technologies for protein detection in complex biological samples.
  • Introduction to effective sample preparation and separation techniques to reduce sample complexity.
  • Overview of essential bioinformatics tools for interpreting large proteomics datasets.
  • Summary of key findings and applications in cancer, heart, and diabetes research.

Conclusions:

  • Mass spectrometry (MS) has revolutionized proteomics, enabling comprehensive protein profiling.
  • Effective sample handling and advanced bioinformatics are crucial for extracting biological insights from proteomics data.
  • Proteomics holds significant promise for advancing research and clinical applications in major diseases like cancer, heart disease, and diabetes.