TAILIEUCHUNG - Managing and Mining Graph Data part 57

Managing and Mining Graph Data part 57 is a comprehensive survey book in graph data analytics. It contains extensive surveys on important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by leading researchers, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. . | 5550 MANAGING AND MINING GRAPH DATA pairs ssiti i c iiijn certain consti amts. It is formed by folding the single-stranded R NA molecule back onto itself and it provides a scaffold for the tertiary structure 82 107fr The secondaay structure fi often modeled with some approxi-maifons as trees 11 34 35 7-4 93 . Since the exact experimental determination of RNA struature is difficult 1331. ecientists often employ computational methods for predicting time sii itiinisi of various biological molecules. These methods provtde a deepeo understanding sti RNAs structural repertoire and thereby help itt identifying new functional RNAs. In Phylogenetics trees are used as a fundamental data structure to represent and ttudy ovoliitionary conaections among different organisms as understood by ancestor-descendant relatianohips. The Tree of Life 3 is an example of such a tree iftustnating tire algyi geny of iffe on Errth ihat is based on the collective evidence from many dtfferent fiefdr of biology and bioscience. The organisms over which a phytogenetic ttee itt mduced are referred to as toa sand they aorm tha leaf noder in the tr 2 2. The internal nodes denote the speciation sand duplicati on rvents whsch result in orthologs sand paralogs respectively. Spe-ciatiof ir the origin of a new specins capable of making a living in a new way arom the fpesies from whScM it more. Paralogs are genes related by duplication within r genomei Whtle traditronai Phylogenetics relied on morphological data obtained by mcsssuring and qusntifying the phenotypic properties of representative organ it mt more recent studies ure gene or amino acid sequences encodzing nncodmg protcint as the basir for classification. There exist a number oO dibfereni approachcr to coaslruct these trees from input data 4 - dtstrnce matiix bir cnf- meShodf maximum parsimony maximum likelihood Bayesian iititriir uti. e c. The trcce produced by these methods can either be rooted or unrootedr Sometimes it is porsible to itiitce

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