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Protein can be represented by amino acid interaction network. This network is a graph whose vertices are
the proteins amino acids and whose edges are the interactions between them. In this paper we have
formalized amino acid interaction network prediction as a multiobjective evolutionary optimization
problem. This formalism is biologically plausible because interactions among amino acids do not depend
only on a single factor like atomic distance but also other factors like torsion angle, hydrophobicity and
hydrophilicity etc. This problem is then solved and implemented using multiobjective genetic algorithm
and subsequently optimized using ant colony optimization technique. The result shows that our algorithm
performs better than recent amino acid interaction network prediction algorithms that are based on single
factor
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