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Python For Bioinformatics (Series in Biomedical Informatics)
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If you need to a good book on bioinformatics algorithms that is language agnostic may I suggest An Introduction to Bioinformatics Algorithms (Computational Molecular Biology) as well as Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. The latter book is especially good for computer science students seeking bioinformatics knowledge. Let me also point out that this book is of use for people seeking Python solutions to non-bioinformatics problems. Since much of bioinformatics has to do with dealing with strings, trees, and statistical analysis of data, students of subjects other than biology can find uses for this book.
Do note that the book's one great problem is that it is using Python 2 not Python 3. It is the fault of the designers of Python that most everything written for Python 2 becomes broken in a Python 3 interpreter rather than the fault of this author, yet the problem remains. Fortunately, Python looks enough like pseudocode that you can probably do any translations necessary without too much hair-pulling.
If you don't know much about Python or Bioinformatics, then this book is probably for you. If you have previous Python experience, I would skip this book.
The idea of the book is to teach algorithms that are useful for real bioinformatic applications, with the hope that you will be creating you own algorithms or applications in the future. Is not a book to learn BioPython (the preface clearly states that and explains why the skills learned in this book an BioPython could be used in a complementary fashion).
The book uses Python 2, not Python 3. This is not a drawback as some people want to think, Python 2 is going to be the "standard" python for at least few year more and many (but not all) of the features of Python 3 are already present in Python 2.7. Even more important the book relies heavily in the NumPy library (as almost all scientific python programming) and NumPy is not, yet, compatible with Python 3, hence using Python 3 in a book like this will be, at least, non-sense.
The only problem is that sometimes with some topics the author does not take too much time to explain the applications of some ideas, for example in the chapter on Hidden Markov Model (HMM) the Author just explain how to program different HMM implementations. Probably this is a mismatch between my background and the author's (I am closer to the a structural-biologist/biophysics) and some concepts are not used in the exactly same way in different scientific branchs, nothing that not can be solved by reading a Wikipedia entry.
You should buy this book if you want to learn to develop bioinformatics solutions.