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

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

60
The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
60
Protein Networks02:26

Protein Networks

4.6K
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
4.6K
Protein Networks02:26

Protein Networks

2.9K
2.9K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

4.2K
4.2K
Ligand Binding and Linkage00:49

Ligand Binding and Linkage

5.8K
Allosteric proteins have more than one ligand binding site; the binding of a ligand to any of these sites influences the binding of ligands to the other sites. When a protein is allosteric, its binding sites are called coupled or linked.  In the case of enzymes, the site that binds to the substrate is known as the active site and the other site is known as the regulatory site. When a ligand binds to the regulatory site, this leads to conformational changes in the protein that can influence...
5.8K
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

301
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
301

You might also read

Related Articles

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

Sort by
Same author

Adaptive multi-omics integration framework for breast cancer survival analysis.

Scientific reports·2025
Same author

Correction to: The effect of personalized intelligent digital systems for self‑care training on type II diabetes: a systematic review and meta‑analysis of clinical trials.

Acta diabetologica·2023
Same author

The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials.

Acta diabetologica·2023
Same author

Random walks on B distributed resting-state functional connectivity to identify Alzheimer's disease and Mild Cognitive Impairment.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology·2021
Same author

SFM: A novel sequence-based fusion method for disease genes identification and prioritization.

Journal of theoretical biology·2015
Same author

A novel method based on physicochemical properties of amino acids and one class classification algorithm for disease gene identification.

Journal of biomedical informatics·2015

Related Experiment Video

Updated: Mar 5, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

16.4K

Mutual information model for link prediction in heterogeneous complex networks.

Hadi Shakibian1, Nasrollah Moghadam Charkari1

  • 1Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran.

Scientific Reports
|March 28, 2017
PubMed
Summary

A new Meta-path based Mutual Information Index (MMI) improves link prediction in complex networks by analyzing information within meta-paths, outperforming existing connectivity-based methods.

More Related Videos

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.8K
Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.6K

Related Experiment Videos

Last Updated: Mar 5, 2026

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

16.4K
Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time
07:12

Using Informational Connectivity to Measure the Synchronous Emergence of fMRI Multi-voxel Information Across Time

Published on: July 1, 2014

12.8K
Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.6K

Area of Science:

  • Network Science
  • Data Mining
  • Information Theory

Background:

  • Existing meta-path based similarity indices for link prediction in heterogeneous complex networks often rely solely on node connectivity degrees.
  • These methods typically require pre-defined, single, and symmetric meta-paths, limiting their flexibility and effectiveness.
  • They fail to fully leverage the rich information contained within diverse meta-paths.

Purpose of the Study:

  • To propose a novel mutual information model for link prediction in heterogeneous complex networks.
  • To introduce the Meta-path based Mutual Information Index (MMI) that addresses limitations of existing methods.
  • To enhance link prediction accuracy by utilizing information derived from meta-paths rather than just connectivity.

Main Methods:

  • Developed a mutual information model incorporating meta-path based link entropy to estimate link likelihood.
  • The Meta-path based Mutual Information Index (MMI) is designed to utilize a set of available meta-paths.
  • This approach measures information flow through paths, diverging from traditional connectivity-based metrics.

Main Results:

  • Experimental results on a Bibliography network demonstrate the effectiveness of the proposed MMI.
  • The MMI achieved high prediction accuracy compared to other popular similarity indices.
  • The model successfully estimates link likelihood by quantifying information within meta-paths.

Conclusions:

  • The Meta-path based Mutual Information Index (MMI) offers a significant advancement in link prediction for heterogeneous complex networks.
  • By focusing on information content within meta-paths, MMI overcomes the limitations of connectivity-dependent indices.
  • MMI provides a more robust and flexible approach for identifying potential links in complex network structures.