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Related Concept Videos

Protein Networks02:26

Protein Networks

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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.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
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Protein Networks02:26

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What is Gene Expression?01:42

What is Gene Expression?

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Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
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What is Gene Expression?01:36

What is Gene Expression?

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A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised  of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then...
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Cell Specific Gene Expression01:58

Cell Specific Gene Expression

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
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Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

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Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
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Modulation of Tau Subcellular Localization as a Tool to Investigate the Expression of Disease-related Genes
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Predicting Essential Proteins by Integrating Network Topology, Subcellular Localization Information, Gene Expression

Wei Zhang, Jia Xu, Xiufen Zou

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |May 17, 2019
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    Summary
    This summary is machine-generated.

    This study introduces TEGS, a novel computational method for identifying essential proteins using protein subcellular localization. TEGS improves prediction accuracy by integrating multiple data sources, outperforming existing methods.

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    Area of Science:

    • Computational Biology
    • Systems Biology
    • Bioinformatics

    Background:

    • Essential proteins are crucial for cellular functions.
    • Identifying essential proteins is vital but challenging.
    • Current computational methods for essential protein prediction have limitations in accuracy.

    Purpose of the Study:

    • To develop a novel computational method for accurate essential protein identification.
    • To introduce protein subcellular localization information as a key feature.
    • To improve upon existing methods by integrating diverse biological data.

    Main Methods:

    • Developed TEGS, a data fusion method integrating network topology, gene expression, GO annotation, and protein subcellular localization.
    • Defined a new metric for protein subcellular localization essentiality.
    • Evaluated TEGS performance on Saccharomyces cerevisiae datasets.

    Main Results:

    • TEGS demonstrated superior performance in identifying essential proteins compared to seven state-of-the-art methods.
    • Performance was validated using true predicted number, jackknife, and precision-recall curves.
    • The method effectively leverages integrated data, including subcellular localization, for enhanced prediction.

    Conclusions:

    • TEGS offers a more accurate and efficient approach for essential protein identification.
    • The integration of protein subcellular localization information significantly enhances prediction accuracy.
    • The developed method provides a valuable tool for biological research and drug discovery.