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subcellular localization data from the human protein atlas  (Human Protein Atlas)

 
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    Structured Review

    Human Protein Atlas subcellular localization data from the human protein atlas
    The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for <t>subcellular</t> localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.
    Subcellular Localization Data From The Human Protein Atlas, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/subcellular+localization+data+from+the+human+protein+atlas/human+protein+atlas+subcellular+localization+data/pmc07518509-49-6-11
    Average 90 stars, based on 1 article reviews
    subcellular localization data from the human protein atlas - by Bioz Stars, 2026-10
    90/100 stars

    Images

    1) Product Images from "Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes"

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes

    Journal: Patterns

    doi: 10.1016/j.patter.2020.100091

    The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for subcellular localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.
    Figure Legend Snippet: The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for subcellular localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.

    Techniques Used: Plasmid Preparation, Diffusion-based Assay

    The List of Cell Types and Tissues Used in This Study (A) The 131 combinations of cell types and tissues. Each color denotes a tissue and the forks for each color represent their corresponding cell types in this study. (B) The list of subcellular domains in this study followed by the number of proteins being expressed in each subcellular domain.
    Figure Legend Snippet: The List of Cell Types and Tissues Used in This Study (A) The 131 combinations of cell types and tissues. Each color denotes a tissue and the forks for each color represent their corresponding cell types in this study. (B) The list of subcellular domains in this study followed by the number of proteins being expressed in each subcellular domain.

    Techniques Used:

    Expression Patterns of MAPSD Brain-Specific Genes at Cell Resolution and Subcellular Domains (A) Frequency of MAPSD original SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (B) Frequency of MAPSD newly identified SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (C) Frequency of MAPSD original SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions. (D) Frequency of MAPSD newly identified SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions.
    Figure Legend Snippet: Expression Patterns of MAPSD Brain-Specific Genes at Cell Resolution and Subcellular Domains (A) Frequency of MAPSD original SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (B) Frequency of MAPSD newly identified SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (C) Frequency of MAPSD original SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions. (D) Frequency of MAPSD newly identified SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions.

    Techniques Used: Expressing

    Related Articles

    Plasmid Preparation:

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes
    Article Snippet: PPI network is then adjusted to include molecular trafficking patterns. .. This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A). .. The rationale behind this adjustment is that if two proteins being connecte

    Diffusion-based Assay:

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes
    Article Snippet: PPI network is then adjusted to include molecular trafficking patterns. .. This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A). .. The rationale behind this adjustment is that if two proteins being connecte

    Expressing:

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes
    Article Snippet: PPI network is then adjusted to include molecular trafficking patterns. .. This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A). .. The rationale behind this adjustment is that if two proteins being connecte



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    subcellular localization data from the human protein atlas  (Human Protein Atlas)
    90
    Human Protein Atlas subcellular localization data from the human protein atlas
    The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for <t>subcellular</t> localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.
    Subcellular Localization Data From The Human Protein Atlas, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/subcellular+localization+data+from+the+human+protein+atlas/human+protein+atlas+subcellular+localization+data/pmc07518509-49-6-11
    Average 90 stars, based on 1 article reviews
    subcellular localization data from the human protein atlas - by Bioz Stars, 2026-10
    90/100 stars
    		  Buy from Supplier

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    The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for subcellular localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.

    Journal: Patterns

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes

    doi: 10.1016/j.patter.2020.100091

    Figure Lengend Snippet: The Structure of MAPSD MAPSD steps include: creating the protein-protein interaction network followed by adjusting it for subcellular localizations; creating the Markov transition distribution matrix, assembling SCZ signatures from genome, epigenome, and transcriptome sources followed by creating the signal vector and adjust it for different tissues and cell types within them; creating tissue/cell-specific interaction networks, and signal diffusion across all of the dedicated networks to measure the disease signal intensities in unannotated proteins. Each dot on the human body scheme denoted the tissue being evaluated.

    Article Snippet: This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A).

    Techniques: Plasmid Preparation, Diffusion-based Assay

    The List of Cell Types and Tissues Used in This Study (A) The 131 combinations of cell types and tissues. Each color denotes a tissue and the forks for each color represent their corresponding cell types in this study. (B) The list of subcellular domains in this study followed by the number of proteins being expressed in each subcellular domain.

    Journal: Patterns

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes

    doi: 10.1016/j.patter.2020.100091

    Figure Lengend Snippet: The List of Cell Types and Tissues Used in This Study (A) The 131 combinations of cell types and tissues. Each color denotes a tissue and the forks for each color represent their corresponding cell types in this study. (B) The list of subcellular domains in this study followed by the number of proteins being expressed in each subcellular domain.

    Article Snippet: This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A).

    Techniques:

    Expression Patterns of MAPSD Brain-Specific Genes at Cell Resolution and Subcellular Domains (A) Frequency of MAPSD original SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (B) Frequency of MAPSD newly identified SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (C) Frequency of MAPSD original SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions. (D) Frequency of MAPSD newly identified SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions.

    Journal: Patterns

    Article Title: Cell-Type-Specific Proteogenomic Signal Diffusion for Integrating Multi-Omics Data Predicts Novel Schizophrenia Risk Genes

    doi: 10.1016/j.patter.2020.100091

    Figure Lengend Snippet: Expression Patterns of MAPSD Brain-Specific Genes at Cell Resolution and Subcellular Domains (A) Frequency of MAPSD original SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (B) Frequency of MAPSD newly identified SCZ risk genes at single-cell resolution to be highly expressed in four brain regions. (C) Frequency of MAPSD original SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions. (D) Frequency of MAPSD newly identified SCZ risk genes at protein level to be highly expressed in various subcellular domains in five cell types across four different brain regions.

    Article Snippet: This adjustment is conducted using the subcellular localization data from the Human Protein Atlas ( A).

    Techniques: Expressing