- Paperback: 152 pages
- Publisher: Dover Publications Inc. (27 Feb 2004)
- Language English
- ISBN-10: 0486435873
- ISBN-13: 978-0486435879
- Product Dimensions: 21.6 x 13.7 x 1 cm
- Average Customer Review: 3.5 out of 5 stars See all reviews (2 customer reviews)
- Amazon Bestsellers Rank: 1,977,789 in Books (See Top 100 in Books)
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Customer Reviews
Most Helpful Customer Reviews
Format:Paperback
A relatively well written book, with particularly good sections on "metrics", measures of similarity, and the neighbour joining algorithm. Unfortunately, being written in the '80's, there is very little mention of DNA-based methods of classification.
It's a good book, but expect nothing on sequence analysis; the Longest Common/Increasing Subsequence algorithms aren't even mentioned.
It's a good book, but expect nothing on sequence analysis; the Longest Common/Increasing Subsequence algorithms aren't even mentioned.
Format:Paperback
This is a well-written book. You can learn a lot from it because it has many good and step by step examples. In my opinion authors of this book successfully provided an understandable introduction to mathematical taxonomy to its audience who are biologist with less mathematical background than engineer and bioinformatist. The content follows a logical path. The first three chapters provide a good introduction to the rest of the chapters, Chapters 4 and 5 have more mathematical nature and discuss principal component analysis and Multidimensional scaling. Mathematics in these two chapters could be presented more clearly. Chapter 6 on cluster analysis is the hart of this book and is written in a simple and understandable language with many good examples. The rest of chapters provide domain application in identification and construction of evolutionary trees. Despite this book was published in 1982, their materials are still quite useful in mathematical biology, classification and clustering. I look forward to see the second edition of this book.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
1 review
Good introduction to classic methods for phylogeny/classification
11 Dec 2011
Format:Paperback
I like this little old book. It gives a simple introduction to characteristic based classification methods. The book is very readable and the math presented is fairly easy to understand. The chapters cover the following:
[1] Introduction
[2] Taxonomic characters
[3] Measures of similarity
[4] Principal components analysis
[5] Multidimensional scaling
[6] Cluster analysis
[7] Identification and assignment techniques
[8] Constructing evolutionary trees
One caveat, because the copyright is old (1982) many more recently developed methods [such as neighbor-joining, maximum likelihood, and Bayesian methods] are not mentioned while others [parsimony] are only mention casually. However the treatment of classic distance clustering methods is fairly good.
[1] Introduction
[2] Taxonomic characters
[3] Measures of similarity
[4] Principal components analysis
[5] Multidimensional scaling
[6] Cluster analysis
[7] Identification and assignment techniques
[8] Constructing evolutionary trees
One caveat, because the copyright is old (1982) many more recently developed methods [such as neighbor-joining, maximum likelihood, and Bayesian methods] are not mentioned while others [parsimony] are only mention casually. However the treatment of classic distance clustering methods is fairly good.
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