Decomposing a biological sequence into modular domains is a basic prerequisite to identifY functional units in biological molecules. The commonly used segmentation procedures usually have two steps: First) collect and align a set of sequences which arc homologous to the target sequence; then parse this multiple alignment into several blocks and identify the functionally important ones by using a semi~ automatic method; which combines manual analysis and expert knowledge. In this paper) we present a novel exploratory approach to parsing and analYlling the above multiple alignment. It is based on an flJlaly-sis~of-variance (ANOYA) type decomposition of the sequence information content. Unlike the traditional change--point method; our approach takes into account not only the composition biases but also the over dispersion effects among the blocks. More generally; our approach provides a better way for judbring some important residues in a protein. Our approach tested on the families of ribosomal proteins has a promising performance. Some subsets of residues critical to these proteins are found.
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