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

Relationship Formation02:12

Relationship Formation

46.3K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
46.3K
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

81
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...
81
Cause and Effect01:53

Cause and Effect

12.7K
While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
12.7K
Protein Networks02:26

Protein Networks

4.7K
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,...
4.7K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

2.1K
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
2.1K
Factors Influencing Attraction III: Similarity01:23

Factors Influencing Attraction III: Similarity

911
The similarity hypothesis suggests that individuals are more likely to form relationships with others who share similar attitudes, beliefs, values, and interests. This concept has been widely studied in social psychology, demonstrating that perceived similarity fosters interpersonal attraction. In an experiment supporting this hypothesis, participants were presented with fabricated information indicating that strangers held attitudes similar to their own. The results showed that participants...
911

You might also read

Related Articles

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

Sort by
Same author

Dolabranes from the Chinese Mangrove, Ceriops tagal.

Journal of natural products·2010
Same author

Electrospinning of small diameter 3-D nanofibrous tubular scaffolds with controllable nanofiber orientations for vascular grafts.

Journal of materials science. Materials in medicine·2010
Same author

Targeting human clonogenic acute myelogenous leukemia cells via folate conjugated liposomes combined with receptor modulation by all-trans retinoic acid.

International journal of pharmaceutics·2010
Same author

The promotion of neural regeneration in an extreme rat spinal cord injury model using a collagen scaffold containing a collagen binding neuroprotective protein and an EGFR neutralizing antibody.

Biomaterials·2010
Same author

Significant evidence of association between polymorphisms in ZNF533, environmental factors, and nonsyndromic orofacial clefts in the Western Han Chinese population.

DNA and cell biology·2010
Same author

[Surgical outcomes of pediatric symptomatic epilepsy and their influencing factors].

Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics·2010

Related Experiment Videos

Efficient network disintegration under incomplete information: the comic effect of link prediction.

Suo-Yi Tan1, Jun Wu1, Linyuan Lü2,3

  • 1College of Information System and Management, National University of Defense Technology, Changsha, Hunan, 410073, P. R. China.

Scientific Reports
|March 11, 2016
PubMed
Summary

Identifying critical nodes for network disintegration is key. This study uses link prediction to improve network collapse prediction, even outperforming complete data in some cases due to a "comic effect".

Related Experiment Videos

Area of Science:

  • Network Science
  • Complex Systems Analysis
  • Data Mining

Background:

  • Network disintegration is crucial for applications like epidemic control and financial stability.
  • Identifying critical nodes is essential for effective network collapse.
  • Real-world networks often suffer from incomplete link information.

Purpose of the Study:

  • To develop an effective method for network disintegration with incomplete link data.
  • To leverage link prediction techniques for identifying critical nodes.
  • To analyze the impact of link prediction on network disintegration performance.

Main Methods:

  • Proposed a novel method for critical node identification using link prediction.
  • Applied link prediction to recover missing links in networks.
  • Conducted extensive experiments on synthetic and real-world networks.

Main Results:

  • Link prediction significantly enhances network disintegration performance.
  • The proposed method effectively identifies critical nodes even with missing information.
  • Observed a
  • comic effect
  • where partial link recovery can outperform complete information.

Conclusions:

  • Link prediction is a valuable tool for improving network disintegration strategies.
  • The
  • comic effect
  • highlights the potential of link prediction in network analysis.
  • This approach offers a robust solution for network control and analysis under data scarcity.