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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 Profiling02:24

Ribosome Profiling

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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.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique...
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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
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Integrating transcriptome and proteome profiling: Strategies and applications.

Dhirendra Kumar1, Gourja Bansal1, Ankita Narang1

  • 1G.N. Ramachandran Knowledge Center for Genome Informatics, CSIR-Institute of Genomics and Integrative Biology, South Campus, Sukhdev Vihar, New Delhi, INDIA.

Proteomics
|June 26, 2016
PubMed
Summary

Integrating transcriptomics and proteomics data offers a comprehensive view of gene regulation. This approach reveals complex biological interactions, aiding in disease marker discovery and drug target identification.

Keywords:
BioinformaticsNetwork biologyPost translational modifications (PTM)ProteogenomicsRNA-seqRibosome profiling

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Understanding cellular states requires analyzing multi-layered gene regulation, including genomic variations, gene expression, and protein modifications.
  • Analyzing these regulatory layers separately limits insights due to their dynamic and complex interplay.

Purpose of the Study:

  • To review methods, studies, and computational tools for the integrative analysis of transcriptomics and proteomics data.
  • To highlight the benefits of unified omics analysis for biological discovery.

Main Methods:

  • Utilizing high-throughput RNA sequencing for transcriptomic data.
  • Employing mass spectrometry (MS) for proteomic data.
  • Applying advanced "big-data" analysis techniques for integrative approaches.

Main Results:

  • Integrative transcriptomic-proteomic analysis provides a more informative understanding of biological systems than analyzing data types separately.
  • Unified omics analyses have proven valuable for genome annotation, RNA-protein quantity prediction, gene regulation deciphering, and identifying disease markers and drug targets.

Conclusions:

  • The integration of transcriptomics and proteomics is crucial for a holistic understanding of gene regulation and biological systems.
  • Various integration strategies exist, tailored to specific research objectives, enhancing biological discovery.