At the intersection of evolutionary biology and theoretical computer science there are two recent books.

• Valiant's "Probably Approximately Correct: Nature's Algorithms for Learning and Prospering in a Complex World", and

• Chaitin's "Proving Darwin: Making Biology Mathematical".

Both books look at evolution through the algorithmic lens, with the first concentrating on how evolution, learning, and intelligence can be all expressed in the PAC-framework of Machine Learning. The second book, looks at how to build a toy model of evolutionary innovation using algorithmic information theory. Although the books are only loosely connected to biology, they do present computer science in a standard pop-sci way and show how it related to more common topics in pop-sci, like evolution.