Amazon.com: Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications (9780195119404): Jason T. L. Wang, Bruce A. Shapiro, Dennis Elliott Shasha: Books
Pattern Discovery in Biomolecular Data and over one million other books are available for Amazon Kindle. Learn more

Have one to sell? Sell yours here
Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications
 
 
Start reading Pattern Discovery in Biomolecular Data on your Kindle in under a minute.

Don't have a Kindle? Get your Kindle here, or download a FREE Kindle Reading App.

Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications [Hardcover]

Jason T. L. Wang (Author), Bruce A. Shapiro (Author), Dennis Elliott Shasha (Author)
4.0 out of 5 stars  See all reviews (1 customer review)


Available from these sellers.


Textbook Student FREE Two-Day Shipping for students on millions of items. Learn more

Formats

Amazon Price New from Used from
Kindle Edition $55.60  
Hardcover --  
Paperback --  

Book Description

November 15, 1999 0195119401 978-0195119404 1
Finding patterns in biomolecular data, particularly in DNA and RNA, is at the center of modern biological research. These data are complex and growing rapidly, so the search for patterns requires increasingly sophisticated computer methods. Pattern Discovery in Biomolecular Data provides a clear, up-to-date summary of the principal techniques. Each chapter is self-contained, and the techniques are drawn from many fields, including graph theory, information theory, statistics, genetic algorithms, computer visualization, and vision. Since pattern searches often benefit from multiple approaches, the book presents methods in their purest form so that readers can best choose the method or combination that fits their needs. The chapters focus on finding patterns in DNA, RNA, and protein sequences, finding patterns in 2D and 3D structures, and choosing system components. This volume will be invaluable for all workers in genomics and genetic analysis, and others whose research requires biocomputing.

Editorial Reviews

About the Author

Jason T. L. Wang is at New Jersey Institute of Technology. Bruce A. Shapiro is at National Cancer Institute.

Product Details

  • Hardcover: 251 pages
  • Publisher: Oxford University Press, USA; 1 edition (November 15, 1999)
  • Language: English
  • ISBN-10: 0195119401
  • ISBN-13: 978-0195119404
  • Product Dimensions: 9.1 x 6.2 x 0.8 inches
  • Shipping Weight: 1.2 pounds
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #3,492,641 in Books (See Top 100 in Books)

 

Customer Reviews

1 Review
5 star:    (0)
4 star:
 (1)
3 star:    (0)
2 star:    (0)
1 star:    (0)
 
 
 
 
 
Average Customer Review
4.0 out of 5 stars (1 customer review)
 
 
 
 
Share your thoughts with other customers:
Most Helpful Customer Reviews

2 of 4 people found the following review helpful:
4.0 out of 5 stars The State-of-the-Art in pattern discovery, October 26, 2000
By A Customer
This review is from: Pattern Discovery in Biomolecular Data: Tools, Techniques, and Applications (Hardcover)
I have studied this book for some time now. The book is clearly directed to researchers in the area of pattern discovery with particular attention to biomolecular data. It collects contributions from the some of the most important research groups in the field. Each chapter is written by a different group but they are all very interesting. I have only a complaint about the quality of the print, not good enough for the cost of the book.
Help other customers find the most helpful reviews 
Was this review helpful to you? Yes No

Share your thoughts with other customers: Create your own review
 
 
 
Only search this product's reviews



Inside This Book (learn more)
First Sentence:
The parsimony method for reconstruction of evolutionary trees (Sober, 1988) and the minimal edit distance method for DNA sequence alignments (e.g., Waterman, 1984) are both based on the principle of Occam's Razor (e.g., Losee, 1980; also known as the Parsimony principle). Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
pattern discovery application, algorithmic mutual information, immediate subpatterns, magic vectors, stem histogram, graph match rules, tree pattern discovery, sequence pattern discovery, inexact graph match, query molecule, block finders, four serine proteases, algorithmic significance method, annealing mutation operator, magic pair, discovered substructure, hash bin, sequence comparison programs, database molecules, stem trace, secondary structure classes, segment conformations, active motifs, motif discovery, rigid group
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Finding Patterns, Half Reg, Start Score Site, Acyl-Carrier Prot, Protein Data Bank, Occam's Razor
New!
Books on Related Topics | Concordance | Text Stats
Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Search Inside This Book:




Tag this product

 (What's this?)
Think of a tag as a keyword or label you consider is strongly related to this product.
Tags will help all customers organize and find favorite items.
Your tags: Add your first tag
 

Customer Discussions

This product's forum
Discussion Replies Latest Post
No discussions yet

Ask questions, Share opinions, Gain insight
Start a new discussion
Topic:
First post:
Prompts for sign-in
 


Active discussions in related forums
Search Customer Discussions
Search all Amazon discussions
   
Related forums


Listmania!


Create a Listmania! list

So You'd Like to...


Create a guide


Look for Similar Items by Category


Look for Similar Items by Subject