Verbose and somewhat entertaining.
A reasonably but not very technical book for the lay reader.
Can live with or without.

Easy to read explains a lot. Puts many things in perspective.

I agree with other reviewers of this book who say that it doesn't deal with any of its topics deeply (as the author says in the book, it's just a summary of conversations he had with the scientists he gives all of about half a page to each, and material he found on the Internet) and that the writing is just a shade above mediocre. The author isn't a bad writer, necessarily, he's just very inconsistent. If he stuck with facts instead of pretending to be a fiction or magazine writer, he'd do well. Also, if he stuck with a British voice and didn't cater to Americans, that would be a good move. If you want to tailor your writing to an American audience, fine--do that and don't make a point of it. Otherwise, stick with your native tendencies, as it tends to make the book more readable.
This book is just ok. A few parts were downright painful, but mainly just because of the writing. The content was never painful, just boring in many places. For anybody with a background in complex adaptive systems, current computer science research, or any of the in vogue areas like network theory or chaos, this book can easily be put aside for others. If you're a layperson just looking for an introduction to the research being done connecting computers and biology, this book might be good. For serious readers, there are better books like 'At Home in the Universe' by Stuart Kauffman (excellent) and 'Complexity' by Mitchell Waldrop (also excellent). Those books are much older, but much more thought-provoking and well-written. They may not cover some of the newest research, but this book covers everything with such lack of depth you won't really get anything more out of reading it.
In short: not a bad book, but could have been much better in writing and content, and serious readers would do better elsewhere.

This book was as primer on how biological structures are being implemented into computer software. The biology sections were generally weak - for example, there are no explanatory diagrams, which I think would have been very helpful to the reader, at least if biology textbooks are trustworthy in their pedagogical methods. Admittedly, there were a few color plates stuck in the middle of the book, but these were more of the gee-whiz variety rather than informative support for the prose. Also Bentley does a lot of name dropping, but does little to specifically outline the projects of those he mentions, sometimes giving merely a paragraph to researchers who are apparently doing "cutting-edge" work in digital biology. Finally, the writing style is inconsistent. Sometimes Bentley writes as if he's a researcher, sometimes as if he's a magazine writer, sometimes as if he's playing short-story fiction writer. This was very distracting. I think the audience that would find this book useful are people who are starting at ground zero in their investigations into computer modeling / implementation of biological structures into computer software. Those with more advanced interests are advised to look elsewhere (cf. Steven Johnson's book on Emergence).

Badly written and not informative.

There are so many "revolutionary" developments in science, and especially in computer science, that it is hard to keep track of them all, and hard feel that they can all be as revolutionary as they claim to be. You have to suspect, though, that if Peter J. Bentley is claiming a revolution, then something wonderful is happening; he is a scientist in the very field of computers, not a reporter, and so his book _Digital Biology: How Nature is Transforming Our Technology and Our Lives_ (Simon & Schuster) is that excellent form of popular science writing, enthusiastic witnessing from an expert in the field. It is obvious that he loves his work, and that it has far-ranging implications, but it is even better that he can communicate the enthusiasm and let the reader share in it.
Digital biology represents a remarkable two way street. Natural processes such as evolution or ant colony behavior can be modeled within a computer to build stronger problem-solving tools. In turn, computer programs can illuminate aspects of behavior of systems large and small in nature, showing just how physics, genes, and evolution have accomplished the complexities we see around us. The best part of Bentley's book is that he has plenty of examples of how these ideas are already at work. Consider what seems to be an inescapable metaphor for brains and for computers, the ant colony. Ants are themselves, like all other insects, tiny robots able to take in small degrees of data and perform small feats of manipulation. One ant is a very limited creature indeed. (Are you getting the analogy? One neuron, too, is practically useless as is one flip-flop gate.) But a mass of ants in a colony starts to show real intelligence. Put a little food out a distance from the colony, and by laying pheromone trails, and following the stronger trails, the huge numbers of ants will in effect calculate the shortest, most efficient way of getting back and forth to it. Making digitally simulated "ants" and electronic "pheromone trails" is already solving difficult problems; "Ant Colony Optimization" is already a respected field in computer science. It has been used to solve the otherwise almost intractable classic Traveling Salesman Problem: A salesman has to get to many different cities on his rounds; what is the most efficient route? Solving this problem took too long for even the fastest of ordinary computers, but letting the digital ants go at it works. It isn't just a matter of solving puzzles, either; such optimization programs are already being applied to communication network routing and electronic circuit design.
In some ways this book is a primer on evolution of different types, and while some fundamentalists continue to make religious objections to evolution in nature, it is obvious from the examples Bentley gives that evolution really does happen in many ways separate from our world of DNA creatures. Bentley draws from examples in many disciplines, and is interested in finding commonalities between them. He demonstrates that from DNA to ants to brains to growth to programming code to evolution to universes, complexity is generated by interactions of similar things, controlled by feedback, and subject to change from the outside. This pattern is more important than the stuff the system is made of. This has not quite the clear universal ring of a Newtonian law, perhaps, but it is certainly an illustrative pattern which is played at all sorts of levels. To Bentley, the pattern is so much more important that the stuff which shows it that he sees no basic difference between biological life and life within a computer. His quickly paced, entertaining book is a good introduction to one of the new ways computers are changing how we look at everything.