Clustering and Classification Methods Used in Biosequence Analysis - Kandemir-Cavas, Cagin;Nasibov, Efendi
32,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 6-10 Tagen
payback
16 °P sammeln
  • Broschiertes Buch

Since human genome studies have brought out a huge number of biosequence data, computational techniques have been developed preventing the vast of cost and time in the management process of these data. In this book, new approaches on clustering and classification methods in biosequence protein, enzyme sequences analysis are studied. Classification is a supervised learning algorithm that aims at categorizing or assigning class labels to a pattern set under the supervision of an expert. Therefore, the prediction of subcellular location of proteins and the classification of enzymes have been…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
Since human genome studies have brought out a huge number of biosequence data, computational techniques have been developed preventing the vast of cost and time in the management process of these data. In this book, new approaches on clustering and classification methods in biosequence protein, enzyme sequences analysis are studied. Classification is a supervised learning algorithm that aims at categorizing or assigning class labels to a pattern set under the supervision of an expert. Therefore, the prediction of subcellular location of proteins and the classification of enzymes have been solved via data mining techniques. Clustering is an unsupervised learning technique that aims at decomposing a given set of elements into clusters based on similarity. Due to the fact that protein sequences have evolutionary relationship, all protein sequences can be organized in terms of their sequence similarity. A graphical illustration called phylogenetic tree can summarize the relationship between the protein sequences. The construction of phylogenetic tree is based on hierarchical clustering. Thus, we have proposed a new method as a linkage method in construction phylogenetic tree.
Autorenporträt
Dr. Kandemir-Cavas has obtained her PhD degree in Statistics in 2010. She is currently an Assistant Professor at the Department of Computer Science at Dokuz Eylül University in Izmir, Turkey.