"alignment matrix" is a correct and usable phrase in written English.
You can use it to refer to a square array of numbers, symbols, or expressions, used especially in mathematics or computing, where numbers, symbols, or expressions on the same line or row have the same significance. For example, the alignment matrix below shows the scores in a two-player game: | Player 1 | Player 2 | |----------|-----------| | 0 | 0 | | 1 | -1 | | -1 | 1 |.
To model evolutionary constraints (not necessary related to folding) imposed on synonymous variability in different genomic positions (e.g. mutational bias) we maintained the distribution of synonymous codons (and thus nucleotides) for each column in the interserotype multiple alignment matrix (matrix containing aligned sequences of 4 serotypes).
When aligning a pair of sequences, the problem can be represented by an alignment matrix.
A common and popular structural alignment method is the DALI, or distance alignment matrix method, which breaks the input structures into hexapeptide fragments and calculates a distance matrix by evaluating the contact patterns between successive fragments.
It then restricts the search by identifying regions (parallelograms in the alignment matrix) containing a number of hits above a given threshold.
For Patser searches, the a priori nucleotide probabilities used to convert the alignment matrix to a weight matrix were set to 0.25 for all 4 nucleotides.
The alignment matrix captures the number of occurrences, ni,j, of letter i at position j across the set of aligned sequences.
Frequency calculations and scoring schemes were adopted from previous algorithms and the positional weights were derived from the alignment matrix itself.
First, the sequences were arranged into an alignment matrix, which defined the number of times each nucleotide was found at a specific position within the alignment.
Among the many imperfections of dealing with an EST-based alignment matrix such as the one in this study, is the randomness of sequencing, which results in suboptimal taxa representation for many of the individual gene partitions.
To improve the accuracy of TMH detection, we developed a machine-learning based predictor, MemBrain, which integrates a number of modern bioinformatics approaches including sequence representation by multiple sequence alignment matrix, the optimized evidence-theoretic K-nearest neighbor prediction algorithm, fusion of multiple prediction window sizes, and classification by dynamic threshold.
