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 computacional com um problema em bioinformática. É um livro muito abrangente, cobre muito bem os tópicos relacionados a alinhamentos e comparações de sequências. Seu capítulo sobre Algoritmos com Grafos é o meu preferido. O autor consegue passar as noções fundamentais com muita simplicidade, de forma que qualquer pessoa possa aprender num ritmo bem rápido.

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

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. The lack of applied problems involving real data was most disappointing. It does have a lot of the type questions that some nerd (me one day :P) might ask you on a job interview. The questions are also a good way to kill time if you have nothing better to do. I give the book credit for stressing dynamic programming. I believe that this is one of the most important concepts in problem solving.

3 stars because I think it is a fairly good introduction for fledgling computer scientists BUT not a good reference for comptuer scientists trying to apply their skills to solve bioinformatic problems.

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.

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.

This is the first book of its type, and it's likely to remain a classic in the field through many editions and many years.