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

Insulin: The Receptor and Signaling Pathways01:28

Insulin: The Receptor and Signaling Pathways

Insulin action is mediated through a receptor tyrosine kinase, akin to the IGF-1 receptor. The number of receptors per cell varies significantly, from 40 on erythrocytes to 300,000 on adipocytes and hepatocytes. The insulin receptor consists of linked α/β subunit dimers, forming a heterotetramer glycoprotein with two extracellular α subunits and two β subunits spanning the membrane. The α subunits inhibit the inherent tyrosine kinase activity of the β subunits, but this inhibition is released...

You might also read

Related Articles

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

Sort by
Same author

GSEA and the coexpression network approach identify novel pathway connections of molecular processes affected in Porto-sinusoidal vascular disease.

PloS one·2026
Same author

Impact of voluntary exercise on obesity-induced brain pathology: Insights from a multimodal approach in male Ldlr-/-.Leiden mice.

Brain, behavior, and immunity·2026
Same author

Epigenomic subtypes of late-onset Alzheimer's disease reveal distinct microglial signatures.

Acta neuropathologica·2026
Same author

Biomaterial Screening Identifies Enhanced Osteogenic and Angiogenic Potential of Mn-Doped Calcium Phosphate Coatings.

ACS biomaterials science & engineering·2026
Same author

Personalisation of the Dutch combined lifestyle intervention SLIMMER improves participant retention and weight loss in people at risk for cardiometabolic disease.

Scientific reports·2025
Same author

Author Correction: Neuroimmune cardiovascular interfaces control atherosclerosis.

Nature·2025
Same journal

Correction to: A quantitative systems pharmacology (QSP) model for Pneumocystis treatment in mice.

BMC systems biology·2019
Same journal

Predicting disease-related phenotypes using an integrated phenotype similarity measurement based on HPO.

BMC systems biology·2019
Same journal

Fusing gene expressions and transitive protein-protein interactions for inference of gene regulatory networks.

BMC systems biology·2019
Same journal

A fast and efficient count-based matrix factorization method for detecting cell types from single-cell RNAseq data.

BMC systems biology·2019
Same journal

GNE: a deep learning framework for gene network inference by aggregating biological information.

BMC systems biology·2019
Same journal

FCMDAP: using miRNA family and cluster information to improve the prediction accuracy of disease related miRNAs.

BMC systems biology·2019
See all related articles

Related Experiment Video

Updated: May 30, 2026

Measurement of Fatty Acid β-Oxidation in a Suspension of Freshly Isolated Mouse Hepatocytes
11:03

Measurement of Fatty Acid β-Oxidation in a Suspension of Freshly Isolated Mouse Hepatocytes

Published on: September 9, 2021

Exploring pathway interactions in insulin resistant mouse liver.

Thomas Kelder1, Lars Eijssen, Robert Kleemann

  • 1Department of Bioinformatics, Maastricht University, Maastricht, The Netherlands. thomaskelder@gmail.com

BMC Systems Biology
|August 17, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method to analyze pathway interactions in complex diseases like insulin resistance. The approach reveals how these interactions change over time and are affected by diet, offering new insights into disease mechanisms.

More Related Videos

Assessing Insulin Clearance in Mice via In Situ Liver Perfusion
07:30

Assessing Insulin Clearance in Mice via In Situ Liver Perfusion

Published on: December 13, 2024

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
08:58

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis

Published on: March 11, 2017

Related Experiment Videos

Last Updated: May 30, 2026

Measurement of Fatty Acid β-Oxidation in a Suspension of Freshly Isolated Mouse Hepatocytes
11:03

Measurement of Fatty Acid β-Oxidation in a Suspension of Freshly Isolated Mouse Hepatocytes

Published on: September 9, 2021

Assessing Insulin Clearance in Mice via In Situ Liver Perfusion
07:30

Assessing Insulin Clearance in Mice via In Situ Liver Perfusion

Published on: December 13, 2024

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis
08:58

Optimized Analysis of In Vivo and In Vitro Hepatic Steatosis

Published on: March 11, 2017

Area of Science:

  • Systems Biology
  • Genomics
  • Metabolomics

Background:

  • Complex phenotypes, such as insulin resistance, involve intricate interactions between multiple biological pathways.
  • Understanding these pathway interactions is crucial for interpreting high-throughput experimental data.

Purpose of the Study:

  • To develop and apply an analysis approach for studying pathway interactions within complex biological datasets.
  • To investigate pathway interactions in insulin-resistant mouse liver following a glucose challenge.

Main Methods:

  • Integrated gene and protein interaction networks with biological pathway information and high-throughput transcriptomics data.
  • Analyzed pathway interactions at different time points post-glucose challenge.
  • Examined underlying protein interactions to identify mechanisms and key proteins involved in pathway cross-talk.

Main Results:

  • Identified numerous pathway interactions in insulin-resistant mouse liver, particularly at baseline (t=0) between different diet groups.
  • Observed an acute stress response at early time points (t=0.6) with overlapping pathway interactions across diet groups.
  • Found distinct pathway interaction networks between diet groups during the late response phase.

Conclusions:

  • Pathway interaction analysis offers a complementary perspective to traditional methods like enrichment analysis.
  • The study provides novel insights into how insulin resistance impacts pathway interactions.
  • The developed analysis approach is broadly applicable to various high-throughput datasets for complex trait analysis.