Going forward¶
Look into¶
Illustrating Python via Bioinformatics Examples (Bioinf-py). At the main site you can select your form.
See here and other resources listed here for current (as of September 2016) information about Jupyter Notebook, which was previously called IPython Notebooks.
Scientific computing: Code alert Nature 541,563-565(2017) doi:10.1038/nj7638-563a Published online 25 January 2017 by Monya Baker
“Graduate students who can incorporate programming into research will have their pick of postdoc positions and other offers, says Schloss. Such skills — or access to people who have them — are increasingly necessary for the big-data questions that scientists want to pursue. “If they think they have a lot of data now, in ten years we are only going to have more,” he says. “If they don’t figure it out now, it’s just going to get worse.”
Article with bottom line supporting learn any language, the important thing is you use it and stick with it, even if you prgress slowly.
Learning Python¶
Rosalind, platform for learning bioinformatics and programming through problem solving
A Whirlwind Tour of Python accompanies a ebook/report of the same name by Jake VanderPlas
Python For Data Science Cheat Sheet - Python Basics, direct link to pdf of sheet only
Python For Data Science: Parts 1 and 2 by Chris Myers - Cornell Center for Advanced Computing & Jeff Sale - San Diego Supercomputing Center - Click ‘next =>’ to step through Part 1 and go back there to get to link to Part 2.
A modern guide to getting started with Data Science and Python
How to Think Like a Computer Scientist: Learning with Python 2.x
How to Think Like a Computer Scientist: Learning with Python 3.x
Recommended reading to get started with Python for science and data analysis
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“The PyData ecosystem is vast and powerful, but it can be overwhelming to newcomers. In this talk I outline some of the history of why the Python data science space is the way it is, as well as what tools and techniques you should focus on to get started for your own problems.”
Scipy Lecture Notes: One document to learn numerics, science, and data with Python
The three Coursera courses in Rice University’s Fundamentals of Computing specialization. The three courses are An Introduction to Interactive Programming in Python, Principles of Computing, and Algorithmic Thinking By the third you are learning little to no new Python and focusing on designing and writing efficient algorithmns, which is useful too. One of the instructors, Luay Nakhleh, focuses on bioinformatics, and so while they touch on some of these aspects later in the series of courses, the main emphasis is computing in general.
Coursera course: Programming for Everybody (Python) - Gradually paced introduction to coding essentials using Python
Bioinformatics and Genomics: IPython and the Systems Biology Knowledgebase
“Why We Built Enthought Canopy, An Inside Look” Recorded Webinar
The GOBLET Training Portal: A Global Repository of Bioinformatics Training Materials, Courses and Trainers, see abstract of associated publication
Keep in mind that Enthought advertises they have free online courses for individuals at degree-granting institutions. the twitter posting said see here. (Although I didn’t see anything about them being free but maybe it is shown after you register with academic email account?)
NCBI with Python¶
NGS Analysis¶
- Titus Brown and Colleagues’ Next-Gen Sequence Analysis Workshops, most recent is Next-Gen Sequence Analysis Workshop (2014). It also has an interesting condensed course he taught last year called 2013 Zero-Entry Workshop: Computational Science for Biologists.
Intermediate Python and Integrating it with Other Tools¶
“Why We Built Enthought Canopy, An Inside Look” Recorded Webinar. Learn about getting Canopy here.
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“The PyData ecosystem is vast and powerful, but it can be overwhelming to newcomers. In this talk I outline some of the history of why the Python data science space is the way it is, as well as what tools and techniques you should focus on to get started for your own problems.”
IPython and Plotly: A Rosetta Stone for MATLAB, R, Python, and Excel plotting
Additional help with plotting biological data via plotly - Exploratory bioinformatics with plot.ly and IPython notebook: Visualizing gene expression data (That notebook on github.)
Python for Economists - primer covering a lot of the essentials
The Jupyter project is the future of the IPython Notebook project. –> An example of integrating it further with Bash.
ADVANCED¶
Go beyond…¶
Filling in Python’s gaps in statistics packages with Rmagic
Comparing Python and R for Data Science
Choosing R or Python for data analysis? An infographic
Shirin Glander’s comparison of R with Python using a practical genomics data example
How I Like to Use Python (or ‘writing Software as a Scientist’)
The Top Mistakes Developers Make When Using Python for Big Data Analytics