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Related Experiment Videos

Tissue microarrays.

Ronald Simon1, Martina Mirlacher, Guido Sauter

  • 1University of Basel, Institut für Pathologie, Schönbeinstrasse 40, Basel, Switzerland. ronald.simon@unibas.ch

Biotechniques
|January 27, 2004
PubMed
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Identifying disease-related genes is crucial. Tissue microarray (TMA) technology enables high-throughput analysis of thousands of tissue samples, accelerating the evaluation of candidate genes for disease research.

Area of Science:

  • Biomedical research
  • Genomics
  • Translational research

Background:

  • Identifying disease-related genes is a key area in modern biomedical research.
  • Advanced molecular profiling techniques enable comprehensive whole-genome screening.
  • Thousands of candidate genes linked to disease development have been identified.

Purpose of the Study:

  • To address the challenge of evaluating numerous candidate genes identified through genomic screening.
  • To introduce and highlight the utility of Tissue Microarray (TMA) technology for high-throughput tissue analysis.
  • To facilitate the process of translational research by enabling efficient evaluation of clinical value.

Main Methods:

  • Utilizing array-based platforms for molecular profiling of disease tissues (e.g., DNA arrays, matrix comparative genomic hybridization).

Related Experiment Videos

  • Employing Tissue Microarray (TMA) technology to array up to 1000 minute tissue samples.
  • Simultaneous analysis of multiple tissue samples in an array format.

    • Main Results:

    • TMA technology allows for high-throughput analysis, keeping pace with rapid lead discovery.
    • The technique enables the analysis of thousands of well-characterized tissue specimens.
    • TMA is a fast, cost-effective, and statistically powerful method.

    Conclusions:

    • Tissue Microarray (TMA) technology significantly facilitates translational research.
    • TMA enables efficient and robust evaluation of candidate disease-related genes.
    • This technology supports the ongoing discovery and validation of genes linked to disease progression.