This book is a very good introduction to the R programming language.
R is a free, general purpose programming language(with a strong support for doing statistics).
The language has its idiosyncrasies. For example, the assignment operator is denoted by a reverse arrow (x<-2); this book does a pretty good job of explaining all these in detail. Once you get past these details, you will find that R is a pretty versatile language.
As a biologist preparing to teach my first course (on Python programming for biologists), I was excited to hear about Mitchell L. Model's Bioinformatics Programming Using Python. A quick look through the table of contents indicated a thorough coverage of the language and useful libraries, and the introduction indicated that it would be appropriate for students in the life sciences with no prior programming experience...
This book is a near-perfect blend of Natural Language Processing done
Python usage to its fullest. Not only did the authors describe NLP
extremely well and provided great explanation to many different
conditions but they also showed an effective use of Python to
substantiate the technical content.
I wanted to like this book. I really did. With all that can be done
doing very interesting things on iPhoneOS devices (both the iPhone
and the iPad) without having to write Objective-C or deal with the App
Comparing to Perl, Python has a quite lagged adoption as the scripting language of choice in the field of bioinformatics, although it is getting some moment recently. If you read job descriptions for bioinformatics engineer or scientist positions a few year back, you barely saw Python mentioned, even as “nice to have optional skill”. One of the reasons is probably lacking of good introductory level bioinformatics books in Python so there are, in general, less people thinking Python as a good choice for bioinformatics. The book “Beginning Perl for Bioinformatics” from O Reilly was published in 2001. Almost one decade later, we finally get the book “Bioinformatics Programming Using Python” from Mitchell Model to fill the gap.
This book is a good Python Programming tutorial. It does a good job of explaining the concepts of Python programming to individuals who would like to learn Python.
The book is written in eleven chapters. It has two appendix titles ‘A’ and ‘B’.
Having worked in configuration management for the last 15 years or so, I've been exposed to most of the mainstream version control systems. Recently I've been using BuildBot and found an fixed some bugs. They use the git revision control system (hosted on github), so it was time to learn something new.