learn-bioinformatics

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learn-bioinformatics

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List of resources for learning bioinformatics, from beginner to advanced

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# learn-bioinformatics

List of resources for learning bioinformatics, from beginner to advanced. The
audience of this list is people who have the desire to get started learning
programming and bioinformatics tools but aren't sure where to start.

As always, the absolute *best* way to learn something is through a **project**.
It is highly recommend that as you learn a new concept in each course, apply
the tool/math/concept to your own data!

## How to contribute

To add to this list of bioinformatics resources, the easiest way is to click "README.md" 
above, then hit the "edit" button (it looks like a pencil):

That will take you to a page that looks like this:

Where you can edit THIS file in the "Markdown" format. Here is a [60-second introduction to Markdown](http://commonmark.org/help/)

Once you're done, scroll to the bottom, add a quick summary of what you added, and click "Propose file change." We'll get back to you shortly!

## What the tags mean

- #book: hardcover or online book that has problems and explanations to follow
  through on your own. Typically larger scale than a #tutorial
- #course: Online or in-person course that you can sign up for with other
  students. In many cases, you can also work through them on your own
- #r: the [R programming language](http://www.r-project.org/)
- #python: the [Python programming language](https://www.python.org/)
- #tutorial: teaches a specific thing to introduce a concept. Typically smaller
  scale than a #book
- #unix: [The Unix command line](https://en.wikipedia.org/wiki/Unix)

## Absolute Beginner

This is for people who may still be "afraid" of the command line and want a
gentle introduction.

- [Data Carpentry](http://www.datacarpentry.org/lessons/) - Introduces
  OpenRefine, R, SQL for data analysis and structure. Can be done on your own
  or you could attend a
  [2-day workshop](http://www.datacarpentry.org/workshops/) near you! #course #tutorial
- [Software Carpentry](https://software-carpentry.org/lessons/) - Introduces
  Unix command line (bash shell), Python, R, Git, SQL for reproducible
  programming and research. Can be done on your own or you could attend a
  [2-day workshop](https://software-carpentry.org/workshops/) near you! #course
  \#tutorial

## Beginner

This is for people who feel ready to hit the ground running

- [Biology meets programming: Bioinformatics for Beginners](https://www.coursera.org/learn/bioinformatics) #course
- [Bioinformatics Computing Course](https://edwardslab.bmcb.georgetown.edu/teaching/bchb524/2016/)
  \#tutorial
- [Coursera "Bioinformatics tag"](https://www.coursera.org/courses?query=bioinformatics&languages=en) #course
- [Genomic Data Science Specialization](https://www.coursera.org/specializations/genomic-data-science),
  especially: #course
  - [Command Line Tools for Genomic Data Science](https://www.coursera.org/learn/genomic-tools)
    #course #unix
- [How to think like a computer scientist](http://www.openbookproject.net/thinkcs/python/english2e/)
  #book
- [Learn Python the Hard Way](https://learnpythonthehardway.org/) #book
- [Practical Computing for Biologists](http://practicalcomputing.org)
- [Python for Biologists](https://pythonforbiologists.com/) - Teaches
  everything an intro Python course would teach, but frames everything in terms
  of biological questions. #book
- [Rosalind](http://rosalind.info/problems/locations/) - List of problems that
  build on each other in complexity, starting from calculating GC content to
  assembling genomes! #problems
- [swirl](http://swirlstats.com/) - Interactive R programming courses in the R
  console #course #r
- [Whirlwind Tour of Python](https://github.com/jakevdp/WhirlwindTourOfPython)#tutorial

## Intermediate

- [Advanced Python for Biologists](https://pythonforbiologists.com/advanced-python-for-biologists/)
  \- the next level of the "Python for Biologists" series #book
- [Rosalind](http://rosalind.info/problems/locations/) - List of problems that
  build on each other in complexity, starting from calculating GC content to
  assembling genomes! #problems
- [Python Data Science Handbook](https://github.com/jakevdp/PythonDataScienceHandbook) #book
- [The Art of Computer Programming](https://www.amazon.com/Computer-Programming-Volumes-1-4A-Boxed/dp/0321751043)
  \- A classic text describing the fundamental algorithms of storing and
  transforming information.
- [Data Structures](https://stepik.org/course/Data-Structures-579) #book
- [How do I learn machine learning?]
  
## Advanced

- [10-minute tutorials for AWS](https://aws.amazon.com/getting-started/tutorials/) #tutorial

learn-bioinformatics

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