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Immunoprecipitation01:20

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Immunogold Electron Microscopy01:20

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Immunoelectron microscopy utilizes immunogold labeling of endogenous proteins with specific antibodies to detect and localize these proteins in cells and tissues. The procedure provides insights into the distribution and quantification of protein under different stimulation conditions offering clues about their functions. Conjugating highly electron-dense gold particles with primary or secondary antibodies allow antigen detection on and within cells, with high resolution and specificity.
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A fluorescence microscope uses fluorescent chromophores called fluorochromes, which can absorb energy from a light source and then emit this energy as visible light. Fluorochromes include naturally fluorescent substances (such as chlorophylls) and fluorescent stains that are added to the specimen to create contrast. Dyes such as Texas red and FITC are examples of fluorochromes. Other examples include the nucleic acid dyes 4’,6’-diamidino-2-phenylindole (DAPI), and acridine orange.
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Immunoinformatics: a brief review.

Namrata Tomar1, Rajat K De

  • 1Machine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Kolkata, 700108, India, namrata_t@isical.ac.in.

Methods in Molecular Biology (Clifton, N.J.)
|July 23, 2014
PubMed
Summary
This summary is machine-generated.

Immunoinformatics, or computational immunology, leverages computer science to analyze vast immunology data, aiding in understanding immune function and disease. This field accelerates research and the development of personalized medicine.

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Area of Science:

  • Immunology
  • Bioinformatics
  • Computational Biology

Background:

  • Exponential growth in immunological, clinical, and epidemiological data from genomic sequencing and literature.
  • Need for advanced computational methods to manage and interpret large-scale immunological datasets.
  • Identification of immunoinformatics as a critical field at the intersection of computer science and immunology.

Purpose of the Study:

  • To review the foundational principles of classical immunology and key immunoinformatics resources.
  • To explore the application of computational immunology in areas such as reverse vaccinology and cancer therapy.
  • To discuss the integration of immunoinformatics with systems biology for advancing personalized medicine.

Main Methods:

  • Review of existing immunological databases and prediction tools.
  • Analysis of computational approaches for understanding immune responses and disease pathogenesis.
  • Exploration of integrated methodologies combining immunoinformatics and systems biology.

Main Results:

  • Immunoinformatics facilitates the analysis of massive datasets, uncovering mechanisms of immune function and disease.
  • Computational tools aid in hypothesis generation for immune responses.
  • Applications demonstrated in reverse vaccinology, immune system modeling, cancer diagnosis, and therapy.

Conclusions:

  • Immunoinformatics is essential for navigating the complexities of modern immunological data.
  • Integration with systems biology promises significant advancements in personalized medicine.
  • The field offers substantial cost and time savings in immunological research and development.