Outline§ Introduction to Python

§ Exercise 5: Getting started in Python

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Programming languages commonly used in bioinformatics:

§ Python (Biopython)§ Perl (BioPerl)§ R (Bioconductor)§ C§ C++§ Java§ Ruby§ MATLAB (Software with GUI)

Bioinformatics programming languages

Scripting languages: general purpose programming languages that support scripts, short programs that automate a task. Typically the code used in scripting languages is interpreted by software during run time, as opposed to lower level languages in which code has to be compiled before execution. 2

Why learn a programming language?

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§ Very versatile.

§ Easy to read syntax (structure of commands) and semantics (meaning

of commands).

§ A high level interpreted language – code is processed at runtime.

§ Python is a great for beginners and advanced programmers.

§ Lots of resources for general programing and computational biology.

§ It’s fun!

§ It’s empowering.

§ It’s a desirable skill that looks good on your CV/resume.

Why Python?

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Python can be used to build just about anything (although not always the best or fastest option)!

§ Backend web development

§ Data analysis

§ Productivity/automation tools

§ Stitching programs together into pipelines

§ Games

§ Apps

What is Python good for?

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Python is easily the top general purpose interpreted language

Open source projects

Perl

Python

Andrew Binstock, 2014

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Goals for the next three class meetings:

1. Become familiar with computer programming concepts.

2. Be able to accomplish some very simple computational tasks using Python.

3. Establish a framework upon which you can learn how to code if you so desire.

Exercise 5:

§ Download Ex 5 and launch it in Jupyter Notebook

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