An algorithm for protein sequences preselection before multiple alignment under a priori uncertainty based on graph theory
A novel approach for protein sequences preselection in the consensus sequence search algorithm before the multiple alignment procedure under a priory uncertainty on the quantitative description of the former experimental results that are used in the original data classification is suggested. The approach is based on the preselection of those sequences that form a global (infinite) cluster in the graph defined by the pairwise identity estimated by a local alignment algorithm just above the percolation threshold. Application of the suggested approach to the multiple alignment of amino acid sequences in proteins of various functional classes that are specifically binded by an intracellular regulatory protein is illustrated.