What is life? This is a question that bothers everyone. Many scientists, including physicists such as Schrödinger, have attempted to explain it using science. Toward the end of the last century, a scientific revolution happened that resulted in the digital biology. The big data of biology may be helpful in answering questions about life; it will also be helpful in creating synthetic life. As Leonard Adleman, the pioneer of deoxyribonucleic acid (DNA) computing, once pointed out: “Biology and computer science--life and computation--are related. I am confident that at their interface great discoveries await those who seek them” [1]. This clearly indicates that in order to understand digital biology, one can also use the tool of computer science. If we see the DNA strings of digital biology as the language of the biology, one has to find the rules or the grammar of the biology. This small (four chapters, postscript, references, and index) but beautiful book is about finding such rules based on the frequencies of A, C, G, and T of the DNA alphabet.

Chapter 1 introduces Chargaff’s first and second parity rules of DNA alphabet frequencies while giving brief background. To get a better insight into these parity rules, chapter 2 models the human base pair frequencies as an optimization problem where Chargaff’s second parity rule (CSPR) and the golden ratio play a major role. This chapter ends with some experimental results using available human genome data. The generalization of CSPR is considered in an elegant manner in chapter 3, with some interesting results with respect to the nucleotide frequencies. The results of chapter 3 are analyzed experimentally using the publicly available genome reference sequences, in chapter 4.

The book ends with an interesting postscript. After reading the book, I can say that the author has a deep understanding of the subject and spent a considerable amount of time thinking about how to present his own discoveries so that the book is accessible to a larger audience. Enough motivation is given at several places, with appropriate quotations and references. I strongly recommend the book to young readers who want to seek discoveries at the interface of computer science and biology.