Introduction to Computational Cancer Biology

A useful guide. The examples assume a particular environment, but that is fixable.

I picked this up after getting stuck on a project and it turned out to be exactly the right book at the right time. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. The index and cross-references are surprisingly good, which matters for a book I will come back to. The chapters on computational biology are the strongest — the examples are stripped down but complete, and I could follow along without constant guessing. Good value for the price and worth the time it takes to work through properly.

Almost excellent. A second edition could easily push it to five stars.

A colleague recommended this and I can see why. It does something that few technical books manage: it respects the reader's time. I appreciated the honesty about what the book does not cover — it saved me from expecting things that were not there. Some of the material is available elsewhere, but rarely presented this clearly. The author is unusually honest about where the simplifications break down, which I appreciated. Recommended, with the caveat that it is not a gentle introduction.

Solid and well-organised. A couple of chapters dragged a little.

There is a particular kind of technical book that is dense without being difficult, and this is one of them. The code samples assume a particular environment, which took a bit of fiddling to get running properly. The book rewards careful reading. Skimming it would be a mistake. Worth picking up if you already have the basics. Set realistic expectations and you will get a lot out of it.