Tiberiu Teşileanu

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Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed "sectors". The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are(More)
We establish that in a large class of strongly coupled (3+1)-dimensional N=1 quiver conformal field theories with gravity duals, adding a chemical potential for the R charge leads to the existence of superfluid states in which a chiral primary operator of the schematic form O=lambdalambda+W condenses. Here lambda is a gluino and W is the superpotential. Our(More)
Localization methods reduce the path integrals in N ≥ 2 supersymmetric Chern-Simons gauge theories on S 3 to multi-matrix integrals. A recent evaluation of such a two-matrix integral for the N = 6 superconformal U (N) × U (N) ABJM theory produced detailed agreement with the AdS/CFT correspondence, explaining in particular the N 3/2 scaling of the free(More)
The CRISPR (clustered regularly interspaced short palindromic repeats) mechanism allows bacteria to adaptively defend against phages by acquiring short genomic sequences (spacers) that target specific sequences in the viral genome. We propose a population dynamical model where immunity can be both acquired and lost. The model predicts regimes where(More)
Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-related circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a(More)
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