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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology by Dan Gusfield

Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology Dan Gusfield ebook
ISBN: 0521585198, 9780521585194
Publisher: Cambridge University Press
Format: djvu
Page: 550

Dna and American Culture The development of techniques to store and search DNA sequences have led to widely applied advances in computer science, especially string searching algorithms, machine learning and database theory. Accordingly, the first part of the book deals with classical methods of sequence analysis: pairwise alignment, exact string matching, multiple alignment, and hidden Markov models. Further knowledge about DNA offers both promises and problems that will only be resolved by the cooperative effort of people in many fields—medicine, law, ethics, social policy, and the humanities—not just molecular biology. Ideally, one would like to construct The computation of phylogenies also has applications in seemingly unrelated areas such as genomic sequencing and finding and understanding genes. Computer Science/Machine Learning: Algorithms on strings, trees, and sequences: computer science and computational biology. Algorithms on strings, trees, and sequences: computer science and computational biology. Algorithms On Strings Trees And Sequences - Gusfield.pdf. Algorithms On Strings, Trees And Sequences - Computer Science And Computational Biology [Cambridge-Press 1997.pdf. In the second part evolutionary time takes center stage a number of key concepts developed by the authors. Chapman & Hall, 3996. Introduction to Computational Biology. ǚ�概念，即一个字符串改变多少个字符可以变成另一个字符串；由俄罗斯人Vladimir Levenshtein提出。 In information theory and computer science, the Levenshtein distance is a metric for measuring the amount of difference between two sequences (i.e. Cell Biology (5219) Plant Sciences (1658) A central computational problem in this field is the construction of a likely phylogeny (genealogical tree) for a set of species based on observed differences in the phenotype, differences in the genotype, or given partial phylogenies. This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists. Cambridge, UK: Cambridge University Press.