The method SPrOS (Specificity Projection On Sequence) is developed to analyze the amino acid sequences related to the same protein family in order to recognize the amino acid residues associated with separated subclasses within this family.

The algorithm SPrOS requires the training set of preliminary classified amino acid sequences. A user should choose the test sequence(s), in which class-specific positions to be predicted. The test sequence is excluded from the training set and compared with all the rest sequences. The obtained positional scores are used as input to the procedure, which estimates the specificity of each query sequence position to each given class

The method provides the specificity estimates Eia, evaluating the specificity of the position i of tested sequence to the class A. The more the Eia value the more the specificity evaluation. The p-values are used to obtain the statistical significance of the Eia estimates. The lower the p-value the more significant Eia.

For more details see SPrOS.pdf. For load/unload example,please, If you have any question, please contact us

Sequence*:
Sequence classification*:
Test Sequence*:

Cutoff p-value:
Frame:
Mode:
* indicates required fields

Result are output to the tab-delimited file containing the rows, each of which present protein identifier, amino acid position number, amino acid type, class identifier, specificity estimation (Eia), p-value for the obtained Eia, and coefficient of belonging of the protein to the given class (predefined in training data). If the calculated p-value is equal to 0.0, then the minimal non-zero value, which can be obtained, is output with the prefix symbol "<". See
result.txt for example

For publication of results please cite the following article: Karasev D.A., Veselovsky A.V., Oparina N.Y., Filimonov D.A., Sobolev B.N. (2016) Prediction of amino acid positions specific for functional groups in a protein family based on local sequence similarity. J. Mol. Recognit. 29(4), 159-169. doi:10.1002/jmr.2515. PubMed PMID: 26549790.