Multidimensional mutual information methods for the analysis of covariation in multiple sequence alignments.

ABSTRACT:

Background

Several methods are available for the detection of covarying positions from a multiple sequence alignment (MSA). If the MSA contains a large number of sequences, information about the proximities between residues derived from covariation maps can be sufficient to predict a protein fold. However, in many cases the structure is already known, and information on the covarying positions can be valuable to understand the protein mechanism and dynamic properties.

Results

In this study we have sought to determine whether a multivariate (multidimensional) extension of traditional mutual information (MI) can be an additional tool to study covariation. The performance of two multidimensional MI (mdMI) methods, designed to remove the effect of ternary/quaternary interdepende

SUBMITTER: Clark GW 

PROVIDER: S-EPMC4046016 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature