Interspecies data mining to predict novel ING-protein interactions in human
2008

Predicting Human Protein Interactions with ING Proteins

publication Evidence: moderate

Author Information

Author(s): Gordon Paul MK, Soliman Mohamed A, Bose Pinaki, Trinh Quang, Sensen Christoph W, Riabowol Karl

Primary Institution: University of Calgary

Hypothesis

Can a cross-species bioinformatics approach identify novel human ING-interacting proteins more accurately than single-species methods?

Conclusion

The study confirms that ING1 interacts specifically with three proteins, linking ING proteins to DNA damage response pathways.

Supporting Evidence

  • ING1 was confirmed to interact with p38MAPK, MEKK4, and RAD50.
  • The interactions link ING proteins to cell stress and DNA damage signaling.
  • None of the validated interactions were predicted by conventional tools.

Takeaway

The researchers found new partners for a protein involved in cancer by looking at data from different species, showing that these proteins work together in important ways.

Methodology

The study used a bioinformatics approach to analyze protein interactions across species, focusing on the ING family of proteins.

Potential Biases

The reliance on low-probability interactions may introduce false positives.

Limitations

The human interactome dataset is not as saturated as that of yeast, which may limit the predictions.

Statistical Information

P-Value

p<0.017

Statistical Significance

p<0.017

Digital Object Identifier (DOI)

10.1186/1471-2164-9-426

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