An amino acid scale is defined by a numerical value assigned to each type of amino acid. The most frequently used scales are the hydrophobicity or hydrophilicity scales and the secondary structure conformational parameters scales, but many other scales exist which are based on different chemical and physical properties of the amino acids. This program provides 50 predefined scales entered from the literature.

You can set several parameters that control the computation of a scale profile, such as the window size, the weight variation model, the window edge relative weight value, and scale normalization.

## Window size

The window size is the length of the interval to use for the profile computation. When computing the score for a given residue*i*, the amino acids in an interval of the chosen length, centered around residue*i*, are considered. In other words, for a window size*n*, we use the*i*- (*n*-1)/2 neighboring residues on each side of residue*i*to compute the score for residue*i*. The score for residue*i*is the sum of the scale values for these amino acids, optionally weighted according to their position in the window.## Relative weight of the window edges

The central amino acid of the window always has a weight of 100%. By default, the amino acids at the remaining window positions have the same weight, but you can make the residue at the center of the window have a larger weight than the others by setting the weight value for the residues at the beginning and end of the interval to a value between 0 and 100%.The decrease in weight between the weight of the center and that of the edges will either be linear or exponential depending on the setting of the

**weight variation model**option.## Weight variation model

In the following example, the window size is 7, and the window edge relative weight value is 10%.- Linear weight variation model
This option divides the weight into equally spaced intervals between 100% and the window edge relative weight (here: 10%).

Weights used for the computation of the score for residue

*i*: (window size 7, weight at window edges 10%) residue number i-3 i-2 i-1 i i+1 i+2 i+3 window position 1 2 3 4 5 6 7 --------------------------------------------------------------------------- weight 10% 40% 70% 100% 70% 40% 10% - Exponential weight variation model
This option makes the weights decrease exponentially from the central position to the window edge. This parameter has an effect only if you set the window edge relative weight to a value other than 100%.

Weights used for the computation of the score for residue

*i*: (window size 7, weight at window edges 10%) residue number i-3 i-2 i-1 i i+1 i+2 i+3 window position 1 2 3 4 5 6 7 --------------------------------------------------------------------------- weight 10% 12% 39% 100% 39% 12% 10%

- Linear weight variation model
## Scale normalization

You can choose whether to use the unmodified selected scale values from the literature or to normalize the values so that they all fit into the range from 0 to 1. Normalization is useful when you want to compare the results of profiles obtained with different scales and makes plots with a more uniform appearance.