An Introduction to Bioinformatics Algorithms [Hardcover]

The flow of the book is excellent. The first few chapters serve as an introduction to computer science basics such as pseudocode, algorithms, and algorithm analysis. These are obviously targeted to those arriving from a biology background. Next comes the molecular biology primer that will serve to introduce biological concepts to those from a computer science background. Each of the chapters in the remainder of the book are organized by type of algorithm, with each chapter containing several biological problems that are addressed by use of that type of algorithm. Again, the organization of the book is excellent.

Following the introductory chapters, the chapters on individual algorithms can be read in any order, although some refer to topics in other chapters to reduce redundancy. Chapter topics are usually introduced using a non-biological example of a biological problem. The algorithm is then described and once understood in terms of the simple problem, the biological problem being addressed using the algorithm becomes immediately apparent. This strategy works extremely well, and the authors even include several little cartoons that serve to illustrate some of the problems.

Admittedly, I was a little hesitant to read a bioinformatics text that contained children's cartoons as illustrations, but I really began to appreciate these as I progressed through parts of the book. They really do make this book fun. There are even cartoon versions of the authors, driving their 'ACME Bioinformatics' Textbook delivery truck that serves to introduce the travelling salesman problem.

As mentioned above, this book is a delight, but only if you possess the right background. If you are a computer science whiz, then its rudimentary treatment of biology and algorithms might be of limited use, although the fact they are organized into algorithmic idea so nicely still should make it worthwhile, if not just to get a taste of the sorts of questions biologists are addressing using computer science. On the other hand, if you are a biologist with little background in computer science or math, understanding some of the algorithms (especially HMMs) might prove difficult. The people who will benefit the most from this book are those with a solid background in biology who understand the fundamentals of mathematics and computer science, but are far from experts in these latter two fields.

Overall, I highly recommend this book to anyone curious about the field of bioinformatics, although it is particularrly suited to certain individuals. This book definitely deserves 5 stars. If you purchase this book, then I hope you enjoy it as much as I did.

Rob.