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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)
 
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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) (Hardcover)

~ Neil C. Jones (Author), Pavel A. Pevzner (Author)
4.6 out of 5 stars  See all reviews (7 customer reviews)

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An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) + Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids + Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology
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Product Description

This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems.

The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively.

An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.

PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Authors' website.

About the Author

Neil C. Jones is a Ph.D. candidate in the Department of Computer Science and Engineering at the University of California, San Diego.

Pavel Pevzner is Ronald R. Taylor Professor of Computer Science at the University of California, San Diego. He is the author of Computational Molecular Biology: An Algorithmic Approach (MIT Press, 2000) .

Product Details

  • Hardcover: 454 pages
  • Publisher: The MIT Press; 1 edition (August 1, 2004)
  • Language: English
  • ISBN-10: 0262101068
  • ISBN-13: 978-0262101066
  • Product Dimensions: 9.1 x 7.2 x 1.1 inches
  • Shipping Weight: 1.9 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (7 customer reviews)
  • Amazon.com Sales Rank: #107,898 in Books (See Bestsellers in Books)

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    #14 in  Books > Science > Biological Sciences > Bioinformatics
    #58 in  Books > Professional & Technical > Professional Science > Evolution > Molecular Biology
    #65 in  Books > Science > Evolution > Molecular Biology

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Neil C. Jones
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Customer Reviews

7 Reviews
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Average Customer Review
4.6 out of 5 stars (7 customer reviews)
 
 
 
 
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59 of 62 people found the following review helpful:
5.0 out of 5 stars Make this your first bioinfo book, October 24, 2004
By wiredweird "wiredweird" (Earth, or somewhere nearby) - See all my reviews
(TOP 100 REVIEWER)   
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It's ironic that a new field like bioinformatics rarely offers any way for newcomers to feel welcome. Bioinformatics is maturing, and this book is that welcome.

It's written as a textbook for a Bioinformatics 101 course, the kind that has both computing and biology students in it. Historically, the two have lived in uneasy truce. The biologists thought that a 'database' was an enzyme that acted on 'datab'. The programmers would, in the authors' words, "spontaneously abort" at the chemistry and informality of biology. Maybe that's less true now, but the authors offer just enough computing basics for the biologists and just enough biology for the computer crowd to be able to discuss the same thing.

After that intro, the authors cover many of the classic problems in bioinformatics, including assembly, motif-finding, clustering, HMMs, dynamic programming, and even mass spec analysis. The style is very readable, and discusses both the biology and the computation of every topic presented. Many algorithms are built up in steps, showing how successive insights from both computation and biology can make existing techniques work better. Along the way, they offer biographical notes about the founders and luminaries of modern biological computation.

This is a great first book for anyone wanting to enter the field, from either a biology or a computer science background. Advanced students will bottom out quickly, and may lose patience with the informal and gently-paced discussion. Sorry, this book was never meant for them. It's a beginner's book, one that respects the intelligence and capability of its reader. It's broad, basic, and detailed enough that modest programming skill will yield working code. This book has my highest recommendation.

//wiredweird
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17 of 19 people found the following review helpful:
4.0 out of 5 stars Excellent algorithms exercise & bioinformatics intro, September 24, 2005
By Yoshiro Aoki (Vancouver, BC / Osaka-Kobe, JP) - See all my reviews
(REAL NAME)   
This is the first book that I've read regarding bioinformatics, so Im updating this as my class moves along. You better have a grasp of basic data structures prior to beginning this book and background with a programming language as there is very little hand-holding in this text. A bio background makes it all more interesting but certainly is not critical. There are no sample code or sources printed with the book nor is there an included CD nor answers to exercises. There is an associated web site where some ideas may be had and errata found/reported, but its not very active that I have seen. The pseudo code in the book is very python-like so easy to make use of. I personally transfer the book's concepts to C/C++ (habit) without much problem, except sometimes my results differ from the book. Apparently these are book bugs, so be sure to check the web site out if unexpected things pop up.
Presently my class is in chapter 8 (of 12) and looking back I would like to caution that some data processing algorithms will drive a computer's CPU quite hard so be aware of battery-munching & heat. My only bones with this book so far are the alphabet soup of variables and lack of answers to exercises. It would be nice if variable definitions were refreshed at the beginning of pseudo code samples.
I like this book as an algorithms text over traditional texts because the applications are much more fascinating. Imagine searching for something and you don't know where that something is. On top of that add not even knowing exactly what it is you are looking for. And when you do find it, its not even in the data searched! This may sound unlikely or even impossible, but it is neither. Rather, its very cool.
4-stars
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13 of 15 people found the following review helpful:
5.0 out of 5 stars A very good introduction!, December 12, 2004
By Zac (USA) - See all my reviews
This book gives a broad overview of algorithmic methods used in bioinformatics. It is well writen and the mathematics needed to understand is undergraduate level. Reading this book makes appetite to apply these methods to problems or to dig deeper in the corresponding method.

Overall, a very good book, and due to its introductory level, one can recommend to all people interested in bioinformatics from all disciplines.
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Most Recent Customer Reviews

5.0 out of 5 stars Uma excelente introdução à bioinformática
Este livro é excelente por várias razões. Entre elas posso citar o fato de estar totalmente voltado ao aprendizado por exemplos, sempre de forma a relacionar um problema... Read more
Published on August 4, 2007 by Rafael S. Assumpcao

3.0 out of 5 stars Should really be called Intro Data Structures and Algorithms
I knew most of the stuff before I opened the first page. It's basically teaching data structures 101 using a few watered down bioinformatic problems for motivation. Read more
Published on July 7, 2005 by Alan Chen

5.0 out of 5 stars The First Undergraduate Text
Bioinformatics is probably the fastest growing field in both biology and computer science. The problems have come from the computer science department and the biology department... Read more
Published on December 6, 2004 by John Matlock

5.0 out of 5 stars Neil Jones and Pavel Pevzner's Book
Wow...this book is great! It is responsible for why I am on this computer...my father bought it as a guide and got a good job with a good salary. They said it was amazing. Read more
Published on August 30, 2004

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