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Subject Item

dbr:Direct_coupling_analysis

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Direct coupling analysis

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Direct coupling analysis or DCA is an umbrella term comprising several methods for analyzing sequence data in computational biology. The common idea of these methods is to use statistical modeling to quantify the strength of the direct relationship between two positions of a biological sequence, excluding effects from other positions. This contrasts usual measures of correlation, which can be large even if there is no direct relationship between the positions (hence the name direct coupling analysis). Such a direct relationship can for example be the evolutionary pressure for two positions to maintain mutual compatibility in the biomolecular structure of the sequence, leading to between the two positions.DCA has been used in the inference of protein residue contacts, RNA structure predict

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dbc:Bioinformatics

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n10:Direct_coupling_analysis?oldid=1040884724&ns=0

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50890026

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22516

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1040884724

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dbr:Multiple_sequence_alignment dbr:Mutual_information dbr:RNA dbr:Evolutionary_pressure dbr:Mean-field_theory dbr:Normal_distribution dbr:Belief_propagation dbr:Protein_structure dbr:Protein_family dbr:Sequence_(biology) dbc:Bioinformatics dbr:Protein_complex dbr:Likelihood_function dbr:Computational_biology dbr:Entropy_(information_theory) dbr:Protein–protein_interaction dbr:Lagrange_multiplier dbr:Ising_model dbr:Biomolecular_structure dbr:Potts_model dbr:Covariance dbr:Statistical_model dbr:Fitness_landscape dbr:Maximum_likelihood_estimation dbr:Protein_structure_prediction dbr:Regularization_(mathematics) dbr:Phylogenetic_tree dbr:Amino_acid dbr:Protein_contact_map dbr:Network_topology dbr:Correlation dbr:Pseudolikelihood dbr:Monomer dbr:Sequence_alignment dbr:Molecular_coevolution dbr:Matrix_norm dbr:Principle_of_maximum_entropy dbr:Prior_probability dbr:Categorical_variable

dbo:abstract

Direct coupling analysis or DCA is an umbrella term comprising several methods for analyzing sequence data in computational biology. The common idea of these methods is to use statistical modeling to quantify the strength of the direct relationship between two positions of a biological sequence, excluding effects from other positions. This contrasts usual measures of correlation, which can be large even if there is no direct relationship between the positions (hence the name direct coupling analysis). Such a direct relationship can for example be the evolutionary pressure for two positions to maintain mutual compatibility in the biomolecular structure of the sequence, leading to between the two positions.DCA has been used in the inference of protein residue contacts, RNA structure prediction, the inference of protein-protein interaction networks and the modeling of fitness landscapes.

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n10:Direct_coupling_analysis