A Functional Network for the Laboratory Mouse
Author Information
Author(s): Guan Yuanfang, Myers Chad L., Lu Rong, Lemischka Ihor R., Bult Carol J., Troyanskaya Olga G.
Primary Institution: Princeton University
Hypothesis
Can a functional network be established for the laboratory mouse using diverse genetic and functional genomic data?
Conclusion
The study successfully presents a functional network for the laboratory mouse that can predict novel functional assignments and network components.
Supporting Evidence
- The network includes probabilistic functional linkages among 20,581 protein-coding genes.
- The study provides experimental evidence for predictions related to the Nanog gene.
- Cross-species comparisons revealed distinct functional characteristics of conserved neighborhoods.
- The network can accurately predict novel functional assignments.
- An interactive web interface is available for exploring the network.
Takeaway
The researchers created a big map showing how mouse proteins work together, which helps scientists understand how genes function and can lead to new discoveries.
Methodology
The study used a Bayesian integration of diverse genetic and functional genomic data to create a functional network.
Potential Biases
Potential biases from the over-representation of certain datasets and the inherent complexity of the mouse genome.
Limitations
The study may have biases due to the reliance on existing datasets and the complexity of mammalian genomes.
Participant Demographics
Laboratory mouse (Mus musculus) used as the model organism.
Statistical Information
P-Value
p<10−10
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website