Genome Clustering: From Linguistic Models to Classification of Genetic Texts: Studies in Computational Intelligence, cartea 286
Autor Alexander Bolshoy, Zeev Volkovich, Valery Kirzhner, Zeev Barzilyen Limba Engleză Paperback – 28 iun 2012
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Paperback (1) | 631.84 lei 6-8 săpt. | |
Springer Berlin, Heidelberg – 28 iun 2012 | 631.84 lei 6-8 săpt. | |
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Springer Berlin, Heidelberg – 19 mai 2010 | 636.70 lei 6-8 săpt. |
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Specificații
ISBN-13: 9783642263408
ISBN-10: 3642263402
Pagini: 240
Ilustrații: 206 p. 67 illus.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.34 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642263402
Pagini: 240
Ilustrații: 206 p. 67 illus.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.34 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Computational Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
Biological Background.- Biological Classification.- Mathematical Models for the Analysis of Natural-Language Documents.- DNA Texts.- N-Gram Spectra of the DNA Text.- Application of Compositional Spectra to DNA Sequences.- Marker-Function Profile-Based Clustering.- Genome as a Bag of Genes – The Whole-Genome Phylogenetics.
Textul de pe ultima copertă
The study of language texts at the level of formal non-semantic models has a long history. Suffice it to say that the well-known Markov chains were first introduced as one of such models. The representation of biological data as text and, consequently, applications of text-analysis models in the field of comparative genomics are substantially newer; nevertheless the methods are well developed. In this book, we try to juxtapose linguistic and bioinformatics models of text analysis. So, it can be read, in a sense, “in two directions” – the book is written so as to appeal to the bioinformatician, who may be interested in finding techniques that had initially appeared in the natural language analysis, and to computational linguist, who may be surprised to discover familiar methods used in bioinformatics. In the presentation of the material, the authors, nevertheless, give preference their professional field - bioinformatics. Therefore, even a specialist in bioinformatics can find something new himself in this book. For example, this book includes a review of the main data mining models generating the text spectra.The chapters of the book assume neither advanced mathematical skills nor beginner knowledge of molecular biology. Relevant biological concepts are introduced in the beginning of the book. Several computer science issues relevant to the topics of the book are reviewed in the three appendices: clustering, sequence complexity, and DNA curvature modeling.
Caracteristici
Presents a general spectrum approach in bioinformatics Written by experts in this field