Locations

Rosalind is a platform for learning bioinformatics and programming through problem solving. Take a tour to get the hang of how Rosalind works. If you don't know anything about programming, you can start at the Python Village. For a collection of exercises to accompany Bioinformatics Algorithms book, go to the Textbook Track. Otherwise you can try to storm the Bioinformatics Stronghold right now. If you are completely new to programming, try these initial problems to learn a few basics about the Python programming language. Bioinformatics Stronghold Discover the algorithms underlying a variety of bioinformatics topics: computational mass spectrometry, alignment, dynamic programming, genome assembly, genome rearrangements, phylogeny, probability, string algorithms and others. Ready-to-use software tools abound for bioinformatics analysis. Bioinformatics Textbook Track

UNIX / Linux Tutorial for Beginners A beginners guide to the Unix and Linux operating system. Eight simple tutorials which cover the basics of UNIX / Linux commands. Introduction to the UNIX Operating System What is UNIX? Files and processes The Directory Structure Starting an UNIX terminal Tutorial One Listing files and directories Making Directories Changing to a different Directory The directories . and .. Recommended UNIX and Linux books If you wish to continue learning Unix, here is a list of good Unix and Linux books, ranging from beginners to advanced. Download This tutorial is available for download so you can work offline.

Sphere Online Judge (SPOJ) Become a Programmer, Motherfucker If you don't know how to code, then you can learn even if you think you can't. Thousands of people have learned programming from these fine books: Learn Python The Hard Way Learn Ruby The Hard Way Learn Code The Hard Way I'm also working on a whole series of programming education books at learncodethehardway.org. Learn C The Hard Way Learn SQL The Hard Way Graphics Programming Language Agnostic NerdDinner Walkthrough Assembly Language Bash Clojure Clojure Programming ColdFusion CFML In 100 Minutes Delphi / Pascal Django Djangobook.com Erlang Learn You Some Erlang For Great Good Flex Getting started with Adobe Flex (PDF) Forth Git Grails Getting Start with Grails Haskell Java JavaScript JavaScript (Node.js specific) Latex The Not So Short Introduction to LATEX (perfect for beginners) Linux Advanced Linux Programming Lisp Lua Programming In Lua (for v5 but still largely relevant)Lua Programming Gems (not entirely free, but has a lot of free chapters and accompanying code) Maven Mercurial Nemerle Nemerle NoSQL Oberon Objective-C

NumericAndScientific/Plotting Over the years many different plotting modules and packages have been developed for Python. For most of that time there was no clear favorite package, but recently matplotlib has become the most widely used. Nevertheless, many of the others are still available and may suit your tastes or needs better. Matplotlib is an Open Source plotting library designed to support interactive and publication quality plotting with a syntax familiar to Matlab users.

Some thoughts about programming language tutorials and books. First, I want to welcome you to "Computer Science for Everyone". I made this course in the hopes that those who are seeking to learn programming would be able to. I realize that this is a complex topic, and it may seem overwhelming at first. Once you learn this skill, you will have many opportunities open to you that were not open before. You may be able to get a better job, or perhaps even to create your own product and start your own company. At the very least, you will have access to far more tools that will enable you to do more than you could do before. When you go through the lessons in this course, I encourage you to go through each lesson word-for-word methodically. Also, do not skip a lesson. So many lessons may seem overwhelming, and if so I want to assure you that while there is a lot of material in this course, I go through it slowly. It may be that in the past you tried to learn programming and couldn't. Very rarely do any of these tutorials explain beyond this. Libraries.

git/github guide All statistical/computational scientists should use git and github, but it can be hard to get started. I hope these pages help. (More blather below.) There are many resources for git and github; my aim is to provide the minimal guide to get started. I love git and github. I use git mostly from the command line on a Mac. I would like all of my statistical/computational collaborators to use git and github, so that we may collaborate more easily. Saunak Sen got me started with version control (using subversion), and Pjotr Prins got me to move from subversion to git, but don’t hold either responsible for any errors in my understanding. If you have suggestions for changes or improvements, submit an issue or fork the repo: Follow the instructions above, “Contribute to someone’s repository.” Also see my tutorials on GNU make, knitr, R packages, making a web site with GitHub Pages, data organization, and reproducible research.

stat545-ubc.github