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This method implements an anytime search algorithm that generates partial plans to feed the negotiation process.
SMOreg (SMO) This method implements the sequential minimal-optimization algorithm for learning a support vector regression model.
In essence, this method implements a test for potentials approaching each other closely in time, yet with the advantage that this method also works under noisy conditions.
This method implements a simple minimization of protein costs for a given optimal biomass production.
This method implements branch-site models that simultaneously allow ω variation across branches and sites.
This method implements branch-site models that simultaneously allow dN/dS variation across branches and sites.
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This method, implemented in a numerical program, is based on a quasi-stationary approach, so that time is not a specific factor in the solution.
We then describe an algorithmic translation of this method, implemented in the kernel of the veriT solver (Bouton et al. (2009)) [9].
An original variant of this method implemented in TRAM is described below.
This method (implemented in Datamonkey,[ 66, 99] ) allowed the screening of Tlr sequences for recombination breakpoints.
This method, implemented in the Bioconductor package CellNOptR (http://www.ebi.ac.uk/saezrodriguez/software.html), provides context-specific models with predictive power.
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