Alignment matrix

Figure 1. Scanning electron micrographs of (a) sheath of aligned matrix produced by low-pressure impregnation, and (b) transversely oriented matrix produced by high-pressure impregnation.

STRUCT AL starts with an arbitrary equivalence of atoms between the two proteins A and B. This equivalence defines a list of corresponding residues (represented by their Cd atoms) that are superimposed with the optimal rigid-body transformation. Once the two proteins are superimposed, the program computes a structure alignment matrix SA. SA(i,j) measures the similarity between residue i of protein A and residue j of protein B, based on a function... 

LTSA seeks to minimise a cost function that minimises the distances between points in the low-dimensional space and the tangent space. As shown in [16], the solution to this minimisation problem is formed by the d smallest eigenvectors of an alignment matrix F. The alignment matrix is found by iteratively summing over all local information matrices ... 

A piezo-composite consists of a piezoelectric active phase and a passive plastic phase [2]. In the 1-3-configuration adopted in our case, piezoelectric rods parallely aligned in thickness direction are imbedded in a three-dimensional plastic matrix (Fig. 1). The distance between the rods has to be chosen inferior to the half wave length of the shear wave in the matrix material ensuring that the whole compound is vibrating as a quasi-homogeneous material. 

Lcularly popular [Taylor and Orengo 1989], The method is so named because it uses two amic programming steps. In the first step, it is necessary to determine the score for each of residues, one from each structure. These scores are used to fill a rectangular H matrix, irich dynamic programming is applied to determine the optimal alignment. 

Strength. Prediction of MMC strength is more compHcated than the prediction of modulus. Consider an aligned fiber-reinforced metal-matrix composite under a load P in the direction of the fibers. This load is distributed between the fiber and the matrix ... 

The Bayesian alternative to fixed parameters is to define a probability distribution for the parameters and simulate the joint posterior distribution of the sequence alignment and the parameters with a suitable prior distribution. How can varying the similarity matrix... 

Zhu et al. [15] and Liu and Lawrence [61] formalized this argument with a Bayesian analysis. They are seeking a joint posterior probability for an alignment A, a choice of distance matrix 0, and a vector of gap parameters. A, given the data, i.e., the sequences to be aligned p(A, 0, A / i, R2). The Bayesian likelihood and prior for this posterior distribution is... 

The second line results from the first, because 0 and A are independent a priori, whereas the score of the alignment A depends on A, and the likelihood of the sequences, given the alignment, depends only on the scoring matrix 0. 

The usual alignment algorithm fixes 0 and A as 0o and Aq, so that the prior is 1 when 0 = 00 and A = Aq and is 0 otherwise. Clearly, if experience justifies this choice or some other nonuniform choice, we can choose an informative prior that biases the calculation to certain values for the parameters or limits them to some likely range. The likelihood is well defined by the alignment model defined by using a similarity matrix and affine gap penalties, so that... 

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