Forum:Web Based Interactive Resources To Learn Programming And/Or Bioinformatics

Question

[Malachi Griffith]

I'm looking for a list of web resources to assist students learning basic bioinformatics and programming skills. A few have been mentioned here already:

• Interactive web to learn R (Try R code school)
• Interactive Perl learning (Perl tuts)
• Project Euler equivalent for bioinformatics? (Project Euler)
• Code Academy (Covers JavaScript, Python, Ruby, etc.)
• Rosalind: A Novel Bioinformatics Education Platform (Rosalind)
• Data Camp - R Tutorials and Data Analysis Courses
• Coursera courses
• Swirl (Learn R in R)
• An Online Bioinformatics Curriculum
• Software Carpentry
• Langmead Lab teaching materials
• Machine learning online tutorial

Am I missing any others?

[Medhat]

learn data analysis interactively

[Gjain]

Coursera Programming, Statistics and Algorithms classes

Answer 1

[Gjain]

There are lots of good courses from Coursera which helped me gain good understanding of programming concepts and implementation in bioinformatics. For example:

• Data analysis with R related courses:
  • Computing for data analysis
  • Data Analysis
• Courses that used python with data analysis:
  • An Introduction to Interactive Programming in Python
  • Introduction to Data Science
  • Computational Molecular Evolution
• Computer science and statistics related courses that play key role in bioinformatics:
  • Algorithms: Design and Analysis
  • Probabilistic Graphical Models
  • Machine Learning
  • Statistics: Making Sense of Data
  • Experimental Genome Science
  • Bioinformatics Algorithms (Part 1)

and many more which are very organized and highly useful. I hope some of them will be useful to other people.

[Medhat]

if you missed to attend the course at the time it was announced can you study it in another time "say that data analysis course finished now can i see the material and study it alone?"

[Gjain]

Some of them yes ... but most of them are offered again (once or twice a year), so you can take the live course.

Answer 2

[Nancy Ouyang]

I like this list, which provides detailed comments on each source and also think about the overall structure.

http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002632

An Online Bioinformatics Curriculum

David B. Searls

Published: September 13, 2012

The last sentence of the article is intriguing:

However, the field of bioinformatics by its nature may offer the best chance for finding ways to involve distance learners directly in ongoing scientific research, and that would seem to be a worthy goal for the burgeoning online education movement.

Answer 3

[Jake]

Please check out Software Carpentry as well. This is a great intro that covers not just programming and data analysis (R/Python), but a lot of crucial stuff that every bioinformatician should know but usually is not covered in courses, such as

• Unix shell
• Git and version control
• Unit testing
• SQL and databases
• Data management and provenance

I also like A Quick Guide to Organizing A Computational Biology Project for organizational techniques that usually have to be learned by experience

Answer 4

[martijn]

On DataCamp.com you can find free interactive courses on data science and R (similar to tryR by code school but a lot more focused) :

• Introduction to R
• Data analysis and statistical inference by a professor from Duke University
• Computational finance

New courses in collaboration with RStudio and Revolution analytics are on the way. Just like a new course on statistics with R (together with a professor from Princeton University), and a course focused on R for SAS users.

Answer 5

[Charles Warden]

I think a lot of good resources have already been mentioned. For my own small contribution, I have collected a list of links that I have found useful:

http://cdwscience.blogspot.com/2013/03/bioinformatics-101.html

Probably need to update some sections, but I think it still gives some useful pointers.

Answer 6

[Obi Griffith]

A couple resources that are missing from this list:

Awesome teaching materials from Langmead Lab: http://www.langmead-lab.org/teaching-materials/

Machine learning (Deep learning) online tutorial: http://ufldl.stanford.edu/tutorial/

A great series of Statistical Data Mining lectures made available by Andrew Moore: http://www.autonlab.org/tutorials/list.html

Answer 7

[dago]

Also in Udemy there are really nice and helpful R, Linux and Python courses.

https://www.udemy.com/

For some of them you have to pay though.