Representing inter-residue dependencies in protein sequences with probabilistic networks.
A new method for representing a local region of a protein sequence as a probabilistic network is proposed. The method produces, from a large number of examples of a local region, a network which describes dependencies that exist among amino acid residues in the region. The network is constructed using the greedy-search algorithm based on the minimum description length (MDL) principle. In our experiments, we construct a probabilistic network of the EF-hand motif domain in calcium-binding proteins. Experimental results show that our method provides a visual aid to understanding the inter-residue dependencies of those regions using a probabilistic network, and the network captures several important features which are peculiar to the motif.
C&C Research Laboratories, NEC Corporation, Kanagawa, Japan.
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Mamitsuka
D000465:Algorithms; D000595:Amino Acid Sequence; D002135:Calcium-Binding Proteins / Q000737:chemistry; D003201:Computers; D016208:Databases, Factual; D005069:Evaluation Studies as Topic; D016013:Likelihood Functions; D008958:Models, Molecular; D015233:Models, Statistical; D015394:Molecular Structure; D016571:Neural Networks, Computer; D011506:Proteins / Q000737:chemistry*
D002135:Calcium-Binding Proteins; D011506:Proteins