The "Informatics" aspect of bioinformatics highlights the computational nature of this field of work. With the necessary use of computing resources, many bioinformatics users find it beneficial to gain familiarity with one or more programming languages. Facility with programming can provide any biologist with the tools necessary to troubleshoot unfamiliar programs, expand functionality, design bespoke programs, and generally become more effective in their bioinformatics pursuits.
But to an experimentalist with little or no exposure to programming, getting started can be a daunting task. Thankfully, there are numerous resources online that are specifically geared towards providing the programming novice with the instruction and tools they need to get comfortable and get started. Some of these are listed below.
Advanced users will be able to program and design their own APIs and user interfaces to provide their data a home on the internet, whether inward or outward facing. This too can be a daunting task to the beginner. Below are some links to entry-level web design
Web Hosts
Free Web Design Tutorials
Lynda.com (Fee-based)
Today, the most commonly used languages for bioinformatics programming are Python, Perl, and R. While you may encounter scripts or software packages in other languages, a beginning bioinformatitician can't go wrong if they spend their time learning one or more of these three.
Learn Perl - a free website with everything you will need to learn the Perl programming language
Beginning Perl - free ebook that teaches the language and how to code with it.
PerlMonks is a community forum for troubleshooting Perl code and getting help and advice. A great place for people with some understanding of the language, but who are struggling with high level concepts to get help.
Perldocs - The best way to learn what any given function or functionality in Perl is to read the documentation for that function. Those are gathered here
Perlop and Perlre - Any Perl programmer will need a close understanding of Operators and Regular Expressions. These two documentations are invaluable and thorough in their explanations of these processes.
R
R is both a language, and a graphical environment for using the language. Think of it as both the App and the OS the App runs in, bundled together. While Python and Perl are incredibly powerful and robust, R includes the ability to generate graphical output, such as charts and graphs, and to manipulate those graphics to make them publication-ready. This makes R an attractive tool for many scientists.
R Studio provides a programming environment for your R coding, and also provides many tools to use.
R Studio Education also provides an Online Learning section, with curated links to many free tutorials for learning beginner, intermediate, and advanced R programming
R Cheat Sheets compile several commands, functions, and R capabilities into ready infographics to have handy while you are programming.
R-Tutor is a free introduction to R based Statistical methods
