Improved Method for Identifying Functionally Linked Proteins
Author Information
Author(s): Cokus Shawn, Mizutani Sayaka, Pellegrini Matteo
Primary Institution: University of California, Los Angeles
Hypothesis
Profiles with many runs are more likely to involve functionally related proteins than profiles in which all the matches are concentrated in one interval of the tree.
Conclusion
The new method allows for more accurate and efficient inference of functional relationships between proteins based on phylogenetic profiles.
Supporting Evidence
- Accounting for runs in phylogenetic profile matches improves our ability to identify functionally related pairs of proteins.
- The networks resulting from the new approach have smaller clusters of co-evolving proteins, making them more useful for inferring functional relationships.
- Our method is orders of magnitude more computationally efficient than full tree-based methods.
Takeaway
The study created a new way to find proteins that work together by looking at their genetic similarities, making it faster and better than older methods.
Methodology
The method computes the probability of two profiles having a certain number of matches using a weighted hypergeometric distribution and accounts for runs of consecutive matches.
Limitations
The method may not separate homologous or parallel complexes effectively.
Statistical Information
P-Value
p<0.05
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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