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 Experiment Videos

Discovering biological guilds through topological abstraction.

Gil Alterovitz1, Marco F Ramoni

  • 1Division of Health Science and Technology, Massachusetts Institute of Technology/HarvardUniversity, Cambridge, MA., USA

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|January 24, 2007
PubMed
Summary

This study introduces a network compression method to summarize complex biological networks, revealing novel

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

SOLVE: A structured orthogonal latent variable framework for disentangling confounding in matrix data.

Biology methods & protocols·2026
Same author

From theory to practice: Harmonizing taxonomies of trustworthy AI.

Health policy OPEN·2024
Same author

Development and Validation of a Machine Learning COVID-19 Veteran (COVet) Deterioration Risk Score.

Critical care explorations·2024
Same author

Tryptophan Metabolism in Alzheimer's Disease with the Involvement of Microglia and Astrocyte Crosstalk and Gut-Brain Axis.

Aging and disease·2024
Same author

Automating Clinical Trial Matches Via Natural Language Processing of Synthetic Electronic Health Records and Clinical Trial Eligibility Criteria.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science·2024
Same author

Transfer Learning for Mortality Prediction in Non-Small Cell Lung Cancer with Low-Resolution Histopathology Slide Snapshots.

Studies in health technology and informatics·2024

Area of Science:

  • Computational Biology
  • Network Science
  • Systems Biology

Background:

  • High-throughput biological data generation yields complex relational networks.
  • Visual interpretation and local topological analysis are insufficient for large networks.
  • Need for methods to abstract global network connectivity for biological insights.

Purpose of the Study:

  • To develop a method for abstracting global network connectivity.
  • To discover new network topological classes based on global similarity.
  • To validate the biological relevance of these classes.

Main Methods:

  • Network abstraction using compression techniques.
  • Identification of a new topological class termed 'guilds'.
  • Validation using an Escherichia coli gene regulation network.

Main Results:

  • A novel approach to network summarization via compression.
  • Discovery of 'guilds' as a new class capturing global connectivity similarity.
  • Guilds demonstrated correspondence to biological function in E. coli.

Conclusions:

  • Network compression provides a powerful tool for understanding complex biological networks.
  • Guilds represent a significant finding, offering insights beyond local network topology.
  • This method facilitates the discovery of functional relationships in biological systems.

Related Experiment Videos