HomeGroupsTalkZeitgeist
Hide this

Results from Google Books

Click on a thumbnail to go to Google Books.

Molecular Evolution: A Statistical Approach…
Loading...

Molecular Evolution: A Statistical Approach

by Ziheng Yang

MembersReviewsPopularityAverage ratingConversations
2None2,551,640NoneNone
Recently added bycjtheb, SciPort

None.

None
Loading...

Sign up for LibraryThing to find out whether you'll like this book.

No current Talk conversations about this book.

No reviews
no reviews | add a review
You must log in to edit Common Knowledge data.
For more help see the Common Knowledge help page.
Series (with order)
Canonical title
Original title
Alternative titles
Original publication date
People/Characters
Important places
Important events
Related movies
Awards and honors
Epigraph
Dedication
First words
Quotations
Last words
Disambiguation notice
Publisher's editors
Blurbers
Publisher series
Original language

References to this work on external resources.

Wikipedia in English (1)

Book description
Haiku summary

Amazon.com Product Description (ISBN 0199602603, Hardcover)

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation.

Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative.

This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.

(retrieved from Amazon Thu, 12 Mar 2015 18:10:48 -0400)

No library descriptions found.

Quick Links

Swap Ebooks Audio
2 wanted

Popular covers

Rating

Average: No ratings.

Is this you?

Become a LibraryThing Author.

 

About | Contact | Privacy/Terms | Help/FAQs | Blog | Store | APIs | TinyCat | Legacy Libraries | Early Reviewers | Common Knowledge | 119,570,481 books! | Top bar: Always visible