MyJournals Home  

RSS FeedsEntropy, Vol. 21, Pages 1000: Phylogenetic Weighting Does Little to Improve the Accuracy of Evolutionary Coupling Analyses (Entropy)

 
 

12 october 2019 17:03:14

 
Entropy, Vol. 21, Pages 1000: Phylogenetic Weighting Does Little to Improve the Accuracy of Evolutionary Coupling Analyses (Entropy)
 


Homologous sequence alignments contain important information about the constraints that shape protein family evolution. Correlated changes between different residues, for instance, can be highly predictive of physical contacts within three-dimensional structures. Detecting such co-evolutionary signals via direct coupling analysis is particularly challenging given the shared phylogenetic history and uneven sampling of different lineages from which protein sequences are derived. Current best practices for mitigating such effects include sequence-identity-based weighting of input sequences and post-hoc re-scaling of evolutionary coupling scores. However, numerous weighting schemes have been previously developed for other applications, and it is unknown whether any of these schemes may better account for phylogenetic artifacts in evolutionary coupling analyses. Here, we show across a dataset of 150 diverse protein families that the current best practices out-perform several alternative sequence- and tree-based weighting methods. Nevertheless, we find that sequence weighting in general provides only a minor benefit relative to post-hoc transformations that re-scale the derived evolutionary couplings. While our findings do not rule out the possibility that an as-yet-untested weighting method may show improved results, the similar predictive accuracies that we observe across conceptually distinct weighting methods suggests that there may be little room for further improvement on top of existing strategies.


 
174 viewsCategory: Informatics, Physics
 
Entropy, Vol. 21, Pages 995: A Study of Brain Neuronal and Functional Complexities Estimated Using Multiscale Entropy in Healthy Young Adults (Entropy)
Entropy, Vol. 21, Pages 999: Recognition of Voltage Sag Sources Based on Phase Space Reconstruction and Improved VGG Transfer Learning (Entropy)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten