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Pattern Classification of Grass Genome Sequences


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  • Product Description

Pattern classification is a very powerful clustering and classification of algorithms consisting of an efficient classifier to classify the genomic data set with high accuracy, time and memory complexity of genomic domain The significance of genome sequence clustering lies on the basics of molecular biology, genome sequence alignment and similarity scores. For sequence dataset, motif string/sequences can be used as a class/ cluster representative. Unsupervised local alignment algorithm is proposed for genome sequences classification and it performs better with global alignment based approaches. Performance of unsupervised motif based clustering algorithm is also evaluated for genome sequences dataset and it also performs well, but the time and space complexities of genome sequences alignment algorithm are quadratic. A simple feature selection technique for reducing the time and space requirements for genome sequence comparison is proposed. It can be used for whole clustering or classifying the genome sequences based on sequence similarity without much reduction in the CA. Incremental clustering for large dataset, analysis of algorithm and properties related to leader based

Product Specifications
SKU :COC17389
AuthorSiddanagouda S. Patil
Number of Pages172
Publishing Year11/30/2012
Edition1 st
Book TypeComputing & information technology
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-26 00:00:00
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