BIOINFORMATICS ALGORITHMS

This book shows how books about algorithms should be written. Every chapter revolves around a specific question of biology (genomics, specifically), which is treated in depth. The progression is just right, explanations make sense, with plenty of useful illustrations. The text offers as little background in genomics as necessary, states problems clearly and exactly, provides algorithms in easy to understand pseudo-code, and while developing a line of reasoning, also offers possibilities to branch out and go deeper to those who want to. The authors transmit a sense of wonder and discovery, appealing to those with an interest in genomics and those with an interest in computer science. It is not a basic introduction to algorithms and data structures, as the treated algorithms relate to a specific application domain. The book references a number of coding exercises, that you can implement and test on Rosalind web-site. Even better, Coursera offers a Bioinformatics series from the same authors as the book; the on-line courses are based on the textbook, and also allow you to follow a nice progression of programming exercise, for which they provide automated unit-tests, pretty much in the programming language of your choice. Around the end of every chapter there is a programming "challenge" that requires you to put together what you have studied, starting from a real-word (or at least, realistic) dataset. The book is beautifully printed and bound in hardcover. It collects both volumes of the previous edition, and a little more. The amount of work and dedication that went into it, and the on-line material, is staggering. Note: I have no affiliation with Active Learning or Coursera.

The book arrived in good shape and as-advertised. It's a great book, too, although (strangely, for a textbook) it has no Index. The authors have a lively style and use storytelling to introduce all concepts. Many difficult algorithms are introduced in easy stages that build on each other with easy-to-follow examples. Impressive. Most illustrations are in color, although the text is too small for me in some of them. Let's hope the next edition has an Index. The lack of an Index hurts usability. Bravo to the authors for producing an unusually readable textbook.

I actually bought this book to get a little more background on the biochemistry of genetics / genomics, and while the book has been written more for the computer scientist than the biology, it actually does a great job explaining both sides of the issues. As far as ease of reading on a complex, technical topic, this book can't be beat. It explains sequencing technology as well as graph theory and motivates the reader to question their assumptions and always take the next step. Highly recommended if you're interested in the topic. The graphics are gorgeous, the digressions are highly useful and everyone will learn something.

This is an amazing textbook for learning bioinformatics, no matter what skill level you start at! I am a college sophomore who's interested in bioinformatics and this book is consistently fun and engaging to work through. The supplemental sections are great and have sent me down many paths of learning about interesting new concepts. Also, the Rosalind problems are a great way to apply what I learned from each section! 'An active learning approach' couldn't be more right. Loving the book and can't wait to see what comes next!

My review for this book would be 5 stars if this book had an index. It does not, therefore it gets 2 stars. The table of contents is excellent, which raises it to 3 stars. The problem lies in trying to refer back to previous topics. That is where an alphabetical topic list would save hours. Even the authors, with their many detours, show that book is not a linear narrative.