Combinatorial Computational Biology of RNA: Pseudoknots and Neutral Networks (Paperback)
  • Combinatorial Computational Biology of RNA: Pseudoknots and Neutral Networks (Paperback)
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Combinatorial Computational Biology of RNA: Pseudoknots and Neutral Networks (Paperback)

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£79.99
Paperback 258 Pages / Published: 02/09/2014
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In this monograph, new combinatorial and computational approaches in the study of RNA structures are presented which enhance both mathematics and computational biology. It begins with an introductory chapter, which motivates and sets the background of this research. In the following chapter, all the concepts are systematically developed. The reader will find * integration of more than forty research papers covering topics like, RSK-algorithm, reflection principle, singularity analysis and random graph theory * systematic presentation of the theory of pseudo-knotted RNA structures including their generating function, uniform generation as well as central and discrete limit theorems * computational biology of pseudo-knotted RNA structures, including dynamic programming paradigms and a new folding algorithm * analysis of neutral networks of pseudo knotted RNA structures and their random graph theory, including neutral paths, giant components and connectivity All algorithms presented are freely available through springer.com and implemented in C. A proofs section at the end contains the necessary technicalities. This book will serve graduate students and researchers in the fields of discrete mathematics, mathematical and computational biology. It is suitable as a textbook for a graduate course in mathematical and computational biology.

Publisher: Springer-Verlag New York Inc.
ISBN: 9781489981479
Number of pages: 258
Weight: 415 g
Dimensions: 235 x 155 x 14 mm
Edition: 2011 ed.


MEDIA REVIEWS

From the reviews:

"This book is devoted to the study of the structure of combinatorial models of the ribonucleic acid (RNA). ... This book can serve as an introduction to the study of combinatorial computational biology as well as a reference of known results and state of the art in this topic." (Ludovit Niepel, Zentralblatt MATH, Vol. 1207, 2011)

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