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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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Protein-protein Interfaces02:04

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Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
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Protein Networks02:26

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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.
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Peptide Identification Using Tandem Mass Spectrometry01:33

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Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
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Updated: Mar 8, 2026

mRNA Interactome Capture from Plant Protoplasts
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Identifying the missing proteins in human proteome by biological language model.

Qiwen Dong1,2, Kai Wang3, Xuan Liu4

  • 1Institute for Data Science and Engineering, East China Normal University, Shanghai, 200062, People's Republic of China. qwdong@sei.ecnu.edu.cn.

BMC Systems Biology
|February 4, 2017
PubMed
Summary

Bioinformatics methods identified 102 potential native human proteins from a list of 616 missing proteins. This approach aids the Human Protein Project by pre-filtering proteins difficult to detect experimentally.

Keywords:
Biological language modelHuman proteomeMissing protein

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Area of Science:

  • Proteomics
  • Bioinformatics
  • Genomics

Background:

  • High-throughput sequencing advances proteomics research in the post-genomics era.
  • Identifying all native-encoding protein sequences is crucial for function and pathway analysis.
  • The Human Protein Project faces challenges in detecting 'missing proteins' experimentally.

Purpose of the Study:

  • To employ bioinformatics methods for pre-filtering missing proteins.
  • To identify potential native human proteins from a list of experimentally challenging candidates.

Main Methods:

  • Utilized n-gram models from Natural Language Processing, drawing analogies between biological sequences and natural language.
  • Analyzed a dataset of 616 missing proteins from the neXtProt database.
  • Performed detailed analysis of predicted structure and function for predicted proteins.

Main Results:

  • Identified 102 proteins with a high probability of being native human proteins using the n-gram model.
  • Compared predicted proteins with existing mass spectrometry datasets, showing good agreement with established databases.
  • Found that some missing proteins are likely membrane or natively disordered proteins.

Conclusions:

  • 102 proteins are identified as potential native gene-coding proteins.
  • Bioinformatics offers a viable approach to overcome experimental detection limitations for missing proteins.
  • The study aids in advancing the goals of the Human Protein Project by identifying candidate proteins.