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User:Christoph n plus one/sandbox/Direct Coupling Analysis

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Direct coupling analysis or DCA is an umbrella term for several methods for analyzing sequence data in Computational Biology.[1] The common idea of these methods is to use statistical modeling to quantify the mutual compatibility between two positions of a biological sequence. This mutual compatibility is supposed to represent a direct relationship between the two positions and to be independent of other positions in the sequence. This is in contrast to measures of correlation, which can be large even if there is no direct relationship between the positions (hence the name direct coupling analysis). Since this mutual compatibility links the positions in the process of evolution, it can be effectively seen as quantifying the molecular coevolution between them. DCA has been used in the inference of protein residue contacts,[1][2][3][4] RNA structure prediction,[5][6] the inference of protein-protein interaction networksCite error: A <ref> tag is missing the closing </ref> (see the help page). tags, these references will then appear here automatically -->

  1. ^ a b Morcos, Faruck, et al. "Direct-coupling analysis of residue coevolution captures native contacts across many protein families." Proceedings of the National Academy of Sciences 108.49 (2011): E1293-E1301.
  2. ^ Kamisetty, Hetunandan, Sergey Ovchinnikov, and David Baker. "Assessing the utility of coevolution-based residue–residue contact predictions in a sequence-and structure-rich era." Proceedings of the National Academy of Sciences 110.39 (2013): 15674-15679.
  3. ^ Ekeberg, Magnus, et al. "Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models." Physical Review E 87.1 (2013): 012707.
  4. ^ Marks, Debora S., et al. "Protein 3D structure computed from evolutionary sequence variation." PLOS One 6.12 (2011): e28766.
  5. ^ De Leonardis, Eleonora, et al. "Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction." Nucleic Acids Research 43.21 (2015): 10444-10455.
  6. ^ Weinreb, Caleb, et al. "3D RNA and Functional Interactions from Evolutionary Couplings." Cell 165.4 (2016): 963-975.
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