Drop the pipette and step away from the Petri dish; it is time to learn some coding!
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The biological sciences are becoming more and more data driven. Technological advancements have led to a huge increase in the generation of biological data. Data analysis, required to extract insights from this data, is often the rate limiting step in biological research. This book will help make your data analysis more effective.
If you want to learn how to use the command line to install and run software this book is for you. The command line is used throughout the book and you will quickly gain familiarity with the most important commands. You will also learn how to install software and how to work on remote machines. The latter will be important if you want to run bioinformatics software on your institutes high performance cluster.
You will learn how to write your own data analysis scripts. The book starts off by explaining fundamental computing concepts, teaching you how to think like a computer. You will then learn how to use Python by creating a script to analyse the GC-content of a bacterial genome. There is also a chapter on data visualisation that teaches you how to work with R. Furthermore, programming best practises are highlighted and explained throughout the book.
Early on you will learn how to use version control to track changes to your projects. Furthermore, the concept of using automation to ensure reproducibility is explored in detail.
Important concepts and jargon are explained as they are introduced. No prior knowledge is required. Just a willingness to learn, experiment and have fun geeking out.
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My name is Tjelvar and I am a biologist that has drifted into computing.
I did my undergraduate and PhD in biochemistry. During my PhD I found myself drifting into computing. This process was largely guided by trial and error and was quite painful. At the time there were not many resources for helping biologists make this transition.
After my PhD I wanted to learn more about professional software development (and chemistry) and got a job as an application scientist at a company that developed software and databases for the pharmaceutical industry. During this time I was fortunate enough to work with great people and learnt lots about coding, programming best practises and software development processes.
After six years the lure of biology and academia became too much and I got a job as a scientific computing lab manager in a world leading plant research institute. In this role I am constantly coming into contact with people that are in the same position I was in 12 years ago; biologists needing to learn more about computing.
This book is my attempt to provide a resource for these biologists drifting into computing.