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

BMC Bioinformatics

Jun 3, 2014

Greg W ClarkDomenico L Gatti

Abstract

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....read more

Mentioned in this Paper

Moebius Syndrome 1
Protein Family
Plain X-ray
Staphylococcal Protein A
Radiographic Imaging Procedure
Two-Parameter Models
Sequence Analysis, Protein
Determination, Sequence Homology
Sequence Alignment
Protein Conformation, beta-Strand
4
67
Paper Details
References
  • References28
  • Citations5
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Multidimensional mutual information methods for the analysis of covariation in multiple sequence alignments

BMC Bioinformatics

Jun 3, 2014

Greg W ClarkDomenico L Gatti

PMID: 24886131

DOI: 10.1186/1471-2105-15-157

Abstract

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....read more

Mentioned in this Paper

Moebius Syndrome 1
Protein Family
Plain X-ray
Staphylococcal Protein A
Radiographic Imaging Procedure
Two-Parameter Models
Sequence Analysis, Protein
Determination, Sequence Homology
Sequence Alignment
Protein Conformation, beta-Strand
4
67

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Paper Details
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