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Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology Dan Gusfield
Publisher: Cambridge University Press

Analyzing massive amounts of data officially became a national priority recently when the White House Office of Science and Technology Policy announced the Big Data Research and Development Initiative. A multi-disciplinary team of University of Missouri researchers rose to the big data challenge when they solved a major biological question by using a groundbreaking computer algorithm to find identical DNA sequences in different plant and animal species. @inproceedings{Duval2012, author = {J.-P. This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists. 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. Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology English | 1997-05-28 | ISBN: 0521585198 | 554 pages | DJVU | 5,2 Mb Traditionally an area of study in. (1997) Algorithms on strings, trees and sequences: computer science and computational biology, Cambridge Univ. Debby Hellebrekers, from Maastricht University Medical Centre, Maastricht, The Netherlands, said that the scientists' findings could have a considerable effect on preventing the transmission of mitochondrial diseases. The computation of statistical indexes containing subword frequency counts, expectations, and scores thereof, arises routinely in the analysis of biological sequences. Computers and Intractibility: A Guide to the Theory of NP-Completeness. In the second part evolutionary time takes center stage a number of key concepts developed by the authors. Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology. Handbook of Algorithms and Data Structures.