Statistics and Probability
-
Introduction to Probability by Blitzstein and Hwang. If you don't know any probability theory, this is the book I'd start with. In fact if you don't know any probability theory and you've just finished by book, this is the next book I'd recommend you read.
-
All of Statistics by Wasserman. A mathy book statistical inference, but very good (and concise).
-
An Introduction to Statistical Learning: with Applications in R by James et al. and it's book, The Elements of Statistical Learning by Hastie et al.. The latter book is quite dense, but is good. The former book is much more practical and highly recommended. The authors of ESLII provide a free PDF copy on their website.
-
Machine Learning: A Probabilistic Perspective by Murphy is one of my favorite books. Even though it's angled at machine learning, it's a good general book on modern applied probability and is directly useful for bioinformatics.
Computer Science
-
Algorithms in a Nutshell by Heineman et al.. A great starter book on the subject.
-
An Introduction to Algorithms, Cormen et al.. A dense reference textbook, but one I keep on my shelf.
-
Algorithms with C Great if you're interested in getting started with C in bioinformatics.
Bioinformatics Algorithms
- Bioinformatics Algorithms by Phillip Compeau and Pavel Pevzner looks to be an absolutely stellar book (seriously, one of the best on the subject I've seen... ever). I'd say this is a terrific next book after Bioinformatics Data Skills.