Item description for Introduction to Computational Biology: An Evolutionary Approach by Bernhard Haubold...
Analysis of molecular sequence data is the main subject of this introduction to computational biology. There are two closely connected aspects to biological sequences: (i) their relative position in the space of all other sequences, and (ii) their movement through this sequence space in evolutionary time. 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. In the second part evolutionary time takes center stage and phylogenetic reconstruction, the analysis of sequence variation, and the dynamics of genes in populations are explained in detail. In addition, the book contains a computer program with a graphical user interface that allows the reader to experiment with a number of key concepts developed by the authors.
This textbook is intended for students enrolled in courses in computational biology or bioinformatics as well as for molecular biologists, mathematicians, and computer scientists.
Promise Angels is dedicated to bringing you great books at great prices. Whether you read for entertainment, to learn, or for literacy - you will find what you want at promiseangels.com!
Est. Packaging Dimensions: Length: 9.13" Width: 6.77" Height: 0.94" Weight: 2.07 lbs.
Release Date Oct 4, 2007
Publisher Birkhäuser Basel
ISBN 3764367008 ISBN13 9783764367008
Availability 79 units. Availability accurate as of Jan 24, 2017 12:44.
Usually ships within one to two business days from La Vergne, TN.
Orders shipping to an address other than a confirmed Credit Card / Paypal Billing address may incur and additional processing delay.
Reviews - What do customers think about Introduction to Computational Biology: An Evolutionary Approach?
try the enclosed GUI program Oct 14, 2006
For some readers, the best attraction of the book is the GUI program that lets you quickly experiment and apply the main ideas. The text is very interdisciplinary, written for diverse audiences, spanning biology, computer science and mathematics. Some aspects of the book may perhaps be too mathematical for some biology readers. Say the Hidden Markov Models, for example. But if you keep at it, you should get able to get the gist of the models. Which is another reason for the usefulness of the GUI. Essentially, so long as you understand the basic math ideas, the GUI lets you sidestep the grotty details and focus on applying the overall models.
It could also be that the book is suitable for a university course. The chapter exercises and accompanying answers are useful, in this regard.