Journal article
Automated tissue analysis -- a bioinformatics perspective
Methods of information in medicine, v 44(1)
2005
PMID: 15778792
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Recent progress in automated tissue analysis (tissomics) provides reproducible phenotypical characterization of histological specimens. We introduce informatics tools to cluster and correlate quantitative tissue profiles with gene expression data. The great potential of synergies between tissue analysis and bioinformatics and its perspectives in medical research and computational diagnostics are discussed.
Key enablers in microscopic imaging and machine vision are reviewed to perform a high-throughput tissue analysis. Methodologies are described and results are demonstrated that support a combined analysis of tissue with gene expression profiles whereby the consideration of individual responses is key.
Comprehensive histomorphometric profiles, extracted using machine vision, provide information regarding the components and heterogeneity of a tissue in a reproducible format amenable to data mining and analysis. Tissue quantitative information can be placed in synergetic context with bioinformatics data, such as gene expression profiles, for a more comprehensive stratification of individual responses. From a bioinformatics point of view tissue data are co-variants that support the identification of candidate genes relevant in tissue injury or disease.
Progress in automated analytics enables the generation of quantitative data about tissue previously limited to visual histopathology. Such reproducible data sets can be statistically correlated and clustered throughout the continuum of bioinformatics. The combined approach supports a system-wide view of biology and has a potential to accelerate developments for a personalized computational diagnosis.
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Details
- Title
- Automated tissue analysis -- a bioinformatics perspective
- Creators
- A Kriete - Drexel UniversityK Boyce - Immune Tolerance Network
- Publication Details
- Methods of information in medicine, v 44(1)
- Publisher
- Thieme; Germany
- Number of pages
- 6
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000228217500006
- Scopus ID
- 2-s2.0-16244364344
- Other Identifier
- 991014877791904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Health Care Sciences & Services
- Medical Informatics