We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
This paper introduces a novel way to detect metrical structure in music. We introduce a way to compute autocorrelation such that the distribution of energy in phase space is prese...
In this paper, we describe a broad class of problems arising in the context of designing codes for DNA computing. We primarily focus on design considerations pertaining to the phen...
Background: The proliferation of structural and functional studies of RNA has revealed an increasing range of RNA's structural repertoire. Toward the objective of systematic ...
Daniela Fera, Namhee Kim, Nahum Shiffeldrim, Julie...
Background: Predicting the three-dimensional structure of a protein from its amino acid sequence is a long-standing goal in computational/molecular biology. The discrimination of ...