Introduction to Computational Cancer Biology

Useful in parts. Fine as a reference, less so as a cover-to-cover read.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The chapters on computational biology are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Some of the material is available elsewhere, but rarely presented this clearly. The code samples assume a particular environment, which took a bit of fiddling to get running properly. Fine, but there are stronger books on the same subject if you look around.

This is the one to get if you are serious about computational biology.

I was looking for something that would bridge the gap between tutorials and proper reference material, and this does that well. The book rewards careful reading. Skimming it would be a mistake. A few of the examples could be more realistic, but the underlying points come across clearly. The index and cross-references are surprisingly good, which matters for a book I will come back to. If you have the prerequisites, this is an easy recommendation. I will be keeping it on my desk rather than the shelf.

I got a lot out of this, even if a few sections felt rushed.

I came to this book already familiar with the basics, and it still had plenty to offer. A couple of chapters felt like they could have been merged, but that is a minor complaint. A few of the examples could be more realistic, but the underlying points come across clearly. It is denser than the page count suggests, and I found myself slowing down around the middle. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.