GAIA: a gram-based interaction analysis tool – an approach for identifying interacting domains in yeast
2009

GAIA: A Tool for Analyzing Protein Interactions

Sample size: 1080 publication 10 minutes Evidence: high

Author Information

Author(s): Kelvin X Zhang, BF Francis Ouellette

Primary Institution: University of British Columbia

Hypothesis

Over-represented gram-gram interactions mediate domain-domain interactions (DDIs) and thus protein-protein interactions (PPIs).

Conclusion

GAIA represents a novel and reliable way to predict DDIs that mediate PPIs.

Supporting Evidence

  • GAIA achieves a true positive rate of 82% and a false positive rate of 21%.
  • The algorithm improves sensitivity from 68% to 82% when using weighted gram pairs.
  • GAIA successfully predicted interactions that were previously validated experimentally.

Takeaway

GAIA is a computer program that helps scientists figure out how proteins interact with each other by looking at small parts of their sequences.

Methodology

GAIA extracts n-grams from protein sequences and identifies interactions based on their frequencies.

Limitations

GAIA is limited by its computational time and may not predict interactions mediated by segments outside known interacting domains.

Participant Demographics

The study focuses on protein interactions in Saccharomyces cerevisiae (budding yeast).

Statistical Information

P-Value

p<0.05

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.1186/1471-2105-10-S1-S60

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