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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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Genomics02:02

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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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Related Experiment Video

Updated: Jul 24, 2025

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Integrative Proteogenomics Using ProteomeGenerator2.

Nathaniel Kwok1,2,3, Zita Aretz1,4, Sumiko Takao1,5

  • 1Molecular Pharmacology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, United States.

Journal of Proteome Research
|July 7, 2023
PubMed
Summary
This summary is machine-generated.

ProteomeGenerator2 (PG2) enhances proteomic analysis by integrating genomic and transcriptomic data to identify noncanonical protein variants. This tool expands the scope of proteomic studies beyond canonical sequences.

Keywords:
comprehensive proteomicsgenomicsproteogenomicstranscriptomics

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Area of Science:

  • Genomics
  • Proteomics
  • Bioinformatics

Background:

  • Advances in nucleic acid sequencing and mass spectrometry enable large-scale biological studies.
  • Current proteomic studies are limited by reliance on canonical protein databases.
  • Genetic and transcriptomic variations lead to diverse protein sequences not typically analyzed.

Purpose of the Study:

  • To develop ProteomeGenerator2 (PG2), an advanced framework for generating comprehensive proteomic databases.
  • To integrate genome and transcriptome sequencing data for identifying noncanonical protein variants.
  • To enhance the analysis of proteomes by including variants beyond canonical sequences.

Main Methods:

  • Developed ProteomeGenerator2 (PG2) based on the ProteomeGenerator framework.
  • Integrated genome and transcriptome sequencing data.
  • Incorporated protein variants including amino acid substitutions, insertions, deletions, noncanonical reading frames, and alternative exons.
  • Benchmarked PG2 using synthetic data and real-world analysis of human leukemia cells.

Main Results:

  • PG2 successfully integrates genomic and transcriptomic data to create comprehensive proteomic databases.
  • The tool identifies and incorporates a wide range of protein variants, including those arising from genetic and transcriptomic variations.
  • Benchmarking demonstrated PG2's utility in analyzing complex proteomes, including those from human leukemia cells.

Conclusions:

  • ProteomeGenerator2 (PG2) significantly advances proteomic analysis by enabling the study of noncanonical protein variants.
  • PG2 offers broad compatibility with existing and emerging sequencing and bioinformatics tools.
  • The open-source availability of PG2 facilitates its integration into diverse research settings for deeper biological insights.