Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A Robust Method for the Unsupervised Scoring of Immunohistochemical Staining.

Entropy (Basel, Switzerland)·2024
Same author

Metabolism and signaling crosstalk in glioblastoma progression and therapy resistance.

Molecular oncology·2023
Same author

N7-methylguanosine methylation of tRNAs regulates survival to stress in cancer.

Oncogene·2023
Same author

Glutamine, MTOR and autophagy: a multiconnection relationship.

Autophagy·2022
Same author

Two parallel pathways connect glutamine metabolism and mTORC1 activity to regulate glutamoptosis.

Nature communications·2021
Same author

Downregulation of Glutamine Synthetase, not glutaminolysis, is responsible for glutamine addiction in Notch1-driven acute lymphoblastic leukemia.

Molecular oncology·2020

Related Experiment Video

Updated: Sep 26, 2025

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
07:54

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Published on: October 25, 2011

18.8K

A Method for Unsupervised Semi-Quantification of Inmunohistochemical Staining with Beta Divergences.

Auxiliadora Sarmiento1, Iván Durán-Díaz1, Irene Fondón1

  • 1Departamento de Teoría de la Señal y Comunicaciones, Universidad de Sevilla, Avda. Descubrimientos S/N, 41092 Seville, Spain.

Entropy (Basel, Switzerland)
|April 23, 2022
PubMed
Summary

This study introduces an automated method for quantifying protein expression in tissue images, reducing bias from manual scoring. The new technique achieves high accuracy, comparable to expert researchers, for reliable biomarker analysis.

Keywords:
beta divergenceeigendecompositionhistopathological imagesnon-negative matrix factorizationsemi-quantitative scoringunsupervised stain separation

More Related Videos

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

12.9K
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.3K

Related Experiment Videos

Last Updated: Sep 26, 2025

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
07:54

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Published on: October 25, 2011

18.8K
Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging
08:40

Quantitation of Protein Expression and Co-localization Using Multiplexed Immuno-histochemical Staining and Multispectral Imaging

Published on: April 8, 2016

12.9K
Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment
11:00

Visualization, Quantification, and Mapping of Immune Cell Populations in the Tumor Microenvironment

Published on: March 25, 2020

17.3K

Area of Science:

  • Biomedical Imaging
  • Computational Pathology
  • Histopathology

Background:

  • Semi-quantitative scoring of immunohistochemistry (IHC) staining in tissue samples is crucial for protein expression analysis.
  • Manual scoring is subjective and prone to observer bias, necessitating objective quantification methods.

Purpose of the Study:

  • To develop a fully automatic and unsupervised method for comparative biomarker quantification in histopathological brightfield images.
  • To overcome the limitations of manual scoring by providing a reproducible and unbiased approach.

Main Methods:

  • A two-stage stain separation approach in optical density space using deconvolution and non-negative matrix factorization (NMF) with beta divergences.
  • Feature vector generation based on chromogen intensity and annotation using k-means clustering with beta divergences.

Main Results:

  • The method robustly discriminates between brown and blue chromogens, independent of color variation or expression level.
  • Experimental validation against expert scoring yielded accuracies ranging from 76.60% to 94.58% for five categories.

Conclusions:

  • The proposed automatic scoring system is definable, reproducible, and produces consistent results for biomarker quantification.
  • This automated approach offers a reliable alternative to manual scoring in research laboratories for protein expression analysis.