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However, since the selection of this specific subset of productions requires additional effort, (2) is also harder to use than (3). For this reason, here, we use (3) to construct an algorithm for generation of test sequences achieving k-sequence coverage. Algorithm 10 uses Algorithm 7 to...
The first step in sequence clustering is the selection of representative proteins with well-studied biochemical properties from each major subfamily of known functions (Section 2). These representative proteins, and the protein(s) to be predicted for function, are expanded through a PSI-BLAST search...
Xiong, P. et al. Protein design with a comprehensive statistical energy function and boosted by experimental selection for foldability.Nat. Commun.5, 1–9 (2014). ArticleGoogle Scholar Xiong, P. et al. Increasing the efficiency and accuracy of the ABACUS protein sequence design method.Bioinformat...
ON/OFF value and the target. The updated toehold position weight matrix was used as input to the next round of optimization, and at the last round of iteration, the final sequence was composed of nucleotides with the highest probabilities in the position weight matrix. At each iteration, ...
analyses in computational biology, such as the inference of phylogenetic relationships among DNA/RNA/protein sequences [1, 2], the prediction of their 3D structures [3], the prediction and comparison of their functions [4–6], and the identification of their sites or regions under selection [...
(all of the four steps) is run on the batch until convergence. Sequences that cannot be assigned to any center are kept in the reservoir. Next, a new batch is read. The main mean shift is run on this batch but without the initialization step and for one iteration only, i.e., ...
The pictures in the first column present different steps of the visual query specification (selection of the objects (a)) and motion definition (b), (c): sequences where a car is passing in front of two houses are searched. The pictures in Figure 12.3 show two frames of the retrieved ...
This makes the selection of test time less flexible. White-noise-like PRBS signals have been traditionally used for nonparametric model identification, such as frequency response estimation and correlation analysis. As will be shown later, white noise signals are not the best test signals for ...
However, the constraint of using k states might be too stringent and in many cases we may not know which is the correct number of states. We would like to have an objective function that balances the likelihood score and the number of states. This is a typical model selection problem, and...