Bioinformatics tissue analysis

  • What are the medical applications of bioinformatics?

    Bioinformatics has proven quite useful in medicine as the complete sequencing of the human genome has helped to unlock the genetic contribution for many diseases.
    Its applications include drug discovery, personalized medicine, preventative medicine and gene therapy..

  • What is the application of bioinformatics in molecular biology?

    Bioinformatics tools aid in comparing, analyzing and interpreting genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology.
    At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology..

  • What is the importance of bioinformatics in biomedical?

    Bioinformatics tools aid in the comparison of genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology.
    At a more integrative level, it helps analyze and catalogue the biological pathways and networks that are an important part of systems biology..

  • What is the role of bioinformatics in biological research?

    It plays a role in the textual mining of biological literature and the development of biological and gene ontologies to organize and query biological data.
    It plays a role in the analysis of gene and protein expression and regulation..

  • Bioinformatics tools aid in comparing, analyzing and interpreting genetic and genomic data and more generally in the understanding of evolutionary aspects of molecular biology.
Progress in automated analytics enables the generation of quantitative data about tissue previously limited to visual histopathology.
Tissue quantitative information can be placed in synergetic context with bioinformatics data, such as gene expression profiles, for a more comprehensive 
TissueInformatics analyzes tissue structure by quantifying the locations of cells and cellular components. The data can be queried for any information visible with the tissue.
TissueInformatics analyzes tissue structure by quantifying the locations of cells and cellular components. The data can be queried for any information visible with the tissue. Here a skin sample is analyzed.

Are heterogeneous tissues used in biomedical studies?

However, heterogeneous tissues are often collected in biomedical studies, which reduce the power in the identification of disease-associated variants and gene expression profiles.
We present deTS, an R package, to conduct tissue-specific enrichment analysis with two built-in reference panels.

How to measure tissue specificity in GTEx data?

For GTEx data, we implemented a previous method ( Finucane et al., 2018) by fitting an ordinary regression model for each gene and computed t -statistics to measure the tissue specificity.
Notably, several tissues in GTEx dataset were biologically related, such as:

  • some brain sub-regions.

    • What is tissue transcriptome data?

    Tissue transcriptome data are often heterogeneous.
    It includes ,the genes that are ubiquitously expressed (e.g. housekeeping genes) and other genes that are expressed in specific tissues.
    Several methods have been developed to identify TSGs from expression profiles.

    Where can I find supplemental data for tissue enrichment analysis?

    Supplementary data are available at Bioinformatics online.
    Supplementary data are available at Bioinformatics online.
    TissueEnrich:

  • Tissue-specific gene enrichment analysis Bioinformatics. 2019 Jun 1;35(11):1966-1967.doi:10.1093/bioinformatics/bty890.
    Authors .
    • Tissue heterogeneity refers to the fact that data generated with biological samples can be compromised by cells originating from other tissues or organs than the target tissue or organ of profiling.
    It can be caused by biological processes, sample contamination, or mistakes in sample labelling.
    Tissue heterogeneity affects commonly used, reference gene expression datasets such as the Genotype-Tissue Expression Project (GTEx).
    Tissue heterogeneity refers to the fact that data generated with biological samples can be compromised by cells originating from other tissues or organs than the target tissue or organ of profiling.
    It can be caused by biological processes, sample contamination, or mistakes in sample labelling.
    Tissue heterogeneity affects commonly used, reference gene expression datasets such as the Genotype-Tissue Expression Project (GTEx).

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