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Related Concept Videos

Proteomics01:33

Proteomics

7.3K
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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Global S-sulfenylation proteome analysis reveals a role of Fd-GOGAT in regulating GABA accumulation during Magnaporthe oryzae infection in rice.

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Related Experiment Video

Updated: Jul 3, 2025

TMT Sample Preparation for Proteomics Facility Submission and Subsequent Data Analysis
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RiceProteomeDB (RPDB): a user-friendly database for proteomics data storage, retrieval, and analysis.

Dong U Woo1, Yejin Lee1, Cheol Woo Min2

  • 1Division of Bio & Medical Bigdata Department (BK4 Program), Gyeongsang National University, 501, Jinju-daero, Jinju-si, Gyeongsangnam-do, 52828, Republic of Korea.

Scientific Reports
|February 13, 2024
PubMed
Summary

Rice proteomics research is advanced by RiceProteomeDB (RPDB), a new database simplifying data analysis. This tool aids in improving rice strains, disease resistance, and yield for global food security.

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Area of Science:

  • Agricultural Science
  • Proteomics
  • Bioinformatics

Background:

  • Rice is a global staple, but its proteomic complexity presents significant challenges for agricultural research and food security.
  • Existing proteomic studies in rice face hurdles in data preprocessing, method selection, and result validation due to unique biological factors.

Purpose of the Study:

  • To address the challenges in rice proteomics and facilitate advancements in crop improvement.
  • To develop a comprehensive and user-friendly platform for managing and analyzing rice proteomics data.

Main Methods:

  • Development of RiceProteomeDB (RPDB), a React+Django database.
  • Implementation of features for data organization, preprocessing, method selection, and result validation.
  • Creation of a web interface for data access, analysis, and exploration of experimental conditions.

Main Results:

  • RiceProteomeDB (RPDB) provides a streamlined platform for rice proteomics data analysis.
  • The database simplifies data management, enabling researchers to conduct analyses and share findings.
  • A user-friendly interface and data sharing capabilities foster collaboration and knowledge dissemination.

Conclusions:

  • RPDB enhances the study of rice proteomics, contributing to breakthroughs in strain improvement, disease resistance, and yield optimization.
  • The platform supports global food security initiatives by advancing rice research.
  • RPDB promotes collaborative research through accessible data and analysis tools.