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Proteins are macromolecules which are virtually involved in all of the life processes. The study of protein structures is of utmost importance in the field of bioinformatics. With the advancement in the field of computational biology, there has been tremendous upsurge in the sequential and the structural data deposition. The structure of a protein depends upon the sequence of the amino acids present in it, although similarity in sequence does not guarantee a similarity in structure. Despite the fact that the three-dimensional structure of protein molecule is very important to predict its functionality, yet the backbone of the searching has been majorly dependent upon the sequences rather than the structures. The leading platforms for searching structural similarity in proteins make use of sequence-based searching or text-based searching but do not provide the desired results. In the current manuscript, a model has been proposed to perform “content-based searching” on protein images. Content-based searching takes into account the visual/structure-based similarity and the information contained in the data sets rather than the traditional sequence-based searching. Intelligent Vision Algorithm has been applied to extract the visual features from the protein images for determining the similarity between two proteins. The proposed search engine model will result in an efficient and fast retrieval of similar protein structures.
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- AMIPRO: A Content-Based Search Engine for Fast and Efficient Retrieval of 3D Protein Structures
S. K. Singh
S. Q. Abbas
- Springer Singapore
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