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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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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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A Clinical Metaproteomics Workflow Implemented within Galaxy Bioinformatics Platform to Analyze Host-Microbiome Interactions Underlying Human Disease
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Galaxy Integrated Omics: Web-based Standards-Compliant Workflows for Proteomics Informed by Transcriptomics.

Jun Fan1, Shyamasree Saha1, Gary Barker2

  • 1From the ‡School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK;

Molecular & Cellular Proteomics : MCP
|August 14, 2015
PubMed
Summary
This summary is machine-generated.

Proteomics informed by transcriptomics (PIT) enhances protein identification. GIO software simplifies complex PIT data analysis for researchers, making it accessible via a web interface.

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Genomics

Background:

  • RNA-sequencing technology enables the creation of sample-specific protein databases for peptide and protein identification, termed proteomics informed by transcriptomics (PIT).
  • PIT is valuable for nonmodel organisms and dynamic proteomes in developmental biology and host-pathogen studies, improving known protein coverage and identifying novel gene products.
  • The complexity of integrating diverse software tools for PIT data analysis impedes its widespread adoption.

Purpose of the Study:

  • To develop a user-friendly software system, GIO, that simplifies proteomics informed by transcriptomics (PIT) analysis.
  • To provide accessible PIT workflows for researchers, particularly bench scientists, through a web interface on the Galaxy platform.
  • To offer flexible and reconfigurable workflows supporting various PIT applications.

Main Methods:

  • Development of the GIO software system integrated with the Galaxy platform.
  • Creation of pre-defined workflows within GIO for four common PIT use cases: standard search, identification without a reference genome, identification with a genome guide, and genome annotation.
  • Implementation of a web interface for simplified access and workflow customization.

Main Results:

  • GIO provides a simplified web interface for complex PIT data analysis.
  • Four distinct workflows are available within GIO, catering to common PIT applications.
  • The system allows for reconfiguration and rearrangement of tools to support additional and novel use cases.

Conclusions:

  • GIO democratizes PIT analysis, making it accessible to a broader range of scientists.
  • The software system overcomes the technical barriers associated with PIT data integration and analysis.
  • GIO enhances the utility of RNA-seq data for proteomic discoveries, especially in challenging biological systems.