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An Introduction to Bioinformatics Algorithms [Print Replica] [Format Kindle]

Neil C. Jones , Pavel A. Pevzner
5.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)

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  • ISBN-10 : 0262101068
  • ISBN-13 : 978-0262101066
  • Edition : 1
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Descriptions du produit

Revue de presse

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

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. --Yoshiro Aoki

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 having such fundamentally different goals. The computer scientists see the computer as an end in itself with no real thought on trying to do something useful with it. The biologists see the computer as just another tool in their laboratory. And the biological problems are huge, massive computers like the new Cray's and large Linux clusters are being devoted to biological applications. This book is intended to fit into the chasm between biology and computer science. It discusses computer the algorithmic principles in terms of practical techniques that make sense to the undergraduate biologist. The book is well suited for a first class for the budding bioinformaticist. Each main chapter in the book first introduces an algorithm, then it discusses the biologically relevant problems that this algorithm addresses, it includes a detailed problem and one or more solutions. Finally the chapter concludes with brief biographical sketches of leading figures in the field. --John Matlock

Présentation de l'éditeur

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 Author's website.

Détails sur le produit


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5.0 étoiles sur 5 The book is very useful 5 février 2010
Format:Relié
I think that this is a book, which needs every person who begin studing bioinformatics. The language is very simple and there is many examples for differents algorithms. The book is not very profound, bur is ideal for understand the basic lines in bioinformatics.
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Amazon.com: 4.7 étoiles sur 5  19 commentaires
5.0 étoiles sur 5 Great introduction 12 avril 2012
Par Sergey Aganezov jr - Publié sur Amazon.com
Format:Relié|Achat vérifié
Great book which is perfect for the students, whose major is either mathematics or computer science. Nice biology intro in the beginning and in the section 8: "Graph Algorithms".

Accurate approach for all the algorithms and theorems, as well as their proofs, keeps an interested reader focused during the whole time of reading. I must admit that all that mathematical parts contain nice off-topics, which help to understand the applications of the described methods and technics. The fact that the book was written by several different authors plays it's strengths. Each author is a pro in the described area, so he or she describes the basics in the both most easy and understandable ways.

Special paragraph has to be written for the special sections after each chapter in the book: Exercises! The best way to learn and understand something is to program it, use it, or analyse it. All of the described above can be found in those exercise sections. Difficulty of the tasks out there vary from easy to extremely difficult ones. The number of tasks that are required to be solved for the best understanding is very individual.

All in all this is one of the books the must be on "must have" list of every student who wants to become a scientist in a bioinformatics field.
1 internautes sur 1 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Concise and Informative 27 février 2013
Par Cyberia - Publié sur Amazon.com
Format:Relié|Achat vérifié
This book does exactly what it set out to do - provide an introduction to bioinformatics. It provides not only simple explanations for some of the common algorithms, but in some cases more deeper mathematics behind the algorithm. The illustrations work for what they are trying to portray, the chapters are organized well taking the reader from the basics of molecular biology and dynamic programming to some more of the advanced concepts such as in hidden markov model. I also enjoyed the sections talking about some of the influential scientists in bioinformatics.

All in all a great introductory book.
82 internautes sur 85 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Make this your first bioinfo book 24 octobre 2004
Par wiredweird - Publié sur Amazon.com
Format:Relié|Achat vérifié
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
5.0 étoiles sur 5 Good choice for an absolute beginner 18 mai 2010
Par TFKhang - Publié sur Amazon.com
Format:Relié|Achat vérifié
I find this book well-written and friendly to people who have not been exposed to algorithmic ideas. Biologists who are keen to understand algorithms that underpin all bioinformatics softwares will get a good dose of confidence after reading this book. To get the best out of this book a reader should test the algorithms explained in the book using a familiar programming language. Experienced people looking to "level-up" their expertise are likely to be disappointed - this is definitely a book for beginner / intermediate level folks.
5.0 étoiles sur 5 Five Stars 20 octobre 2015
Par marcos - Publié sur Amazon.com
Format:Relié|Achat vérifié
this is a great book
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