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The network alignment problem in its abstract form can be formulated as an optimization problem with the goal of identifying an optimal mapping between the nodes of the input networks, which maximizes both sequence similarity of aligned proteins and conservation of their underlying interactions.
Nonlinear programming algorithms typically proceed by making a sequence of guesses of the variable vector x (known as iterates and distinguished by superscripts x1, x2, x3, …) with the goal of eventually identifying an optimal value of x.
There are two principal barriers in the process of identifying an optimal façade solution.
probability of false-alarm (Pfa) is the probability of identifying an optimal encoder but not the true one; 3.
Network design problems (NDP) consist of identifying an optimal subgraph of a graph, subject to side constraints.
Fifteen such decavalent bispecific molecules, termed decabodies, were constructed and characterized for the purpose of identifying an optimal decabody design.
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We propose a stochastic optimization-based method to identify an optimal subset of measured variables for process monitoring.
The optimization step aims to identify an optimal setup of sample assignments from multiple candidates.
Once the model is defined, our optimization approach assigns characters to locations on the keyboard, identifies an optimal cursor duration, and considers a variety of cursor paths.
The underlying optimization procedure is based on an empirical scoring scheme designed to identify an optimal hydrogen bonding network.
Voxel-compression mapping works by using a computer to identify an optimal fit between two images.
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