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Related Experiment Videos

CellCircuits: a database of protein network models.

H Craig Mak1, Mike Daly, Bianca Gruebel

  • 1Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92037, USA.

Nucleic Acids Research
|December 1, 2006
PubMed
Summary

CellCircuits is a new open-access database featuring 2019 molecular network models. This systems biology resource aids researchers in exploring functional subnetworks and hypotheses across multiple organisms.

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Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Existing databases often focus on individual molecular interactions or validated pathways, creating a gap in comprehensive network modeling.
  • Screening molecular interaction networks using expression, phenotypic, structural, or conservation data yields functional subnetworks.
  • There is a need for a centralized repository to organize and access these derived network models.

Purpose of the Study:

  • To introduce CellCircuits, an open-access database of molecular network models.
  • To bridge the gap between interaction databases and pathway databases by cataloging computationally derived models.
  • To provide a resource for theorists and experimentalists to share, validate, and search for network models and hypotheses.

Main Methods:

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  • Collected 2019 computationally derived molecular network models from 11 journal articles.
  • Included models spanning five organisms: yeast, worm, fly, Plasmodium falciparum, and human.
  • Made models available as images and in machine-readable formats, with querying by protein names or biological functions.

Main Results:

  • The initial release of CellCircuits catalogs 2019 molecular network models.
  • Models are derived from various network screening approaches.
  • The database supports querying by proteins and biological functions.

Conclusions:

  • CellCircuits serves as a novel systems biology resource by consolidating diverse molecular network models.
  • The database facilitates meta-analyses not feasible with existing resources.
  • It acts as a clearinghouse for model distribution, revision, and hypothesis exploration.