Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

@article{Fatakia2009ComputingHC,
  title={Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors},
  author={Sarosh N Fatakia and Stefano Costanzi and C. Channing Chow},
  journal={PLoS ONE},
  year={2009},
  volume={4},
  pages={97 - 101}
}
G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A… CONTINUE READING
Tweets
This paper has been referenced on Twitter 1 time. VIEW TWEETS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 13 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 125 REFERENCES

Similar Papers

Loading similar papers…