A family of evolution-entropy hybrid methods for ranking protein residues by importance.

By I. Mihalek, I. Res, Olivier Lichtarge. Journal of Molecular Biology, 2004

302 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/58e8b6704e8085a9f77cfdf7b4292b4ff4c7c488

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Citations in the corpus

Learning protein constitutive motifs from sequence data (2018, methodology): “Benchmarking on Lattice Proteins Lattice protein (LP) models were introduced in the 90′s to study protein folding and designMirny and Shakhnovich (2001). In one of thosemodels Shakhnovich and Gutin (1990), a ‘protein’ ofN = 27 amino acids may fold into ∼ 105 distinct structures on a 3 × 3 × 3 cubic ”
ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules (2016, methodology): “The best established alternative to ConSurf for the detection of functional regions is the Evolutionary Trace method and variants thereof (6–8, 21, 22).”
Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure (2009, background): “, traversing phylogenetic trees [28,29], statistical rate inference [26], analysis of functional subfamilies [9,12], and phylogenetic motifs [30].”
Emerging methods in protein co-evolution (2013, methodology): “Evolutionary trace has been improved by calculating a score on the basis of the weighted entropy of a position in all the possible subfamilies defined by the nodes of the corresponding phylogenetic tree 56 (a method called rvET, for ‘real value evolutionary trace’).”
Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification (2010, background): “…groups density [2], sequence analysis (conservation, patterns, conserved blocks along the sequence, evolution, entropy, among others) [3,4,5,6,7,8], sequence and structure properties [9,10,11], evolution and 3D structure information [12,13,14,15], neural networks [16], 3D structure…”
PhosContext2vec: a distributed representation of residue-level sequence contexts and its application to general and kinase-specific phosphorylation site prediction (2018, background): “It is a feature used for quantifying the conservation of potential phosphorylation sites 24 .”
Determinants of protein function revealed by combinatorial entropy optimization (2007, unknown): “subfamily but differ between subfamilies [7-18].”