coding style

 

https://github.com/trekhleb/state-of-the-art-shitcode

repl.it. zero setup online pair coding

 

https://blog.repl.it/intel

CORGIS Datasets Project, virginia tech

CORGIS Datasets Project

The Collection of Really Great, Interesting, Situated Datasets

virginia tech
https://think.cs.vt.edu/corgis/

machine learning, resources

李宏毅
https://www.youtube.com/channel/UC2ggjtuuWvxrHHHiaDH1dlQ/feed

JAX computational genomics tools

On the academic side:

We will be using a number of genomic analysis software packages/tools. Please try to download and install the tools/programs listed below (IGV, R/RStudio and Python).  Ada Zhan (cc’ed here) can assist you with installation questions. We will also be able to provide support on the first day of the course. We will use a cloud computing environment (web-based) but you will get information on that platform just before the course.

If you do not have a laptop at your disposal please alert me ASAP so that we can prepare a machine for your use.

Please install the following:

Integrative Genomics Viewer: (IGV) (Broad Institute)

Please go to the Broad institute website here and download the IGV version for your Mac or PC.

R:

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio   To install on:

Windows:

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

Mac OS X:

Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux:

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install the  RStudio IDE.

Python:  To set  up Python:

Python is a popular language for scientific computing and data science, as well as being a great for general-purpose programming. Installing all of the scientific packages individually can be a bit difficult, so we recommend an using an all-in-one installer, like Anaconda.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.4 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

Windows

• Download and install Anaconda.
• Download the default Python 3 installer. Use all of the defaults for installation except make sure to check Make Anaconda the default Python.

Mac OS X

• Download and install Anaconda.
• Download the default Python 3 installer. Use all of the defaults for installation.

Linux

We recommend the all-in-one scientific Python installerAnaconda.

1. Download the installer that matches your operating system and save it in your home folder. Download the default Python 3 installer.
2. Open a terminal window.
3. Type

bash Anaconda-

and then press tab. The name of the file you just downloaded should appear.

4. Press enter. You will follow the text-only prompts. When there is a colon at the bottom of the screen press the down arrow to move down through the text. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).

AI courese

http://course.fast.ai/ . Python notebook

http://wiki.fast.ai/index.php/How_to_use_the_Provided_Notebooks


https://github.com/fastai/courses/tree/master/deeplearning1/nbs

UML tools, materials

UML tools

https://en.wikipedia.org/wiki/List_of_Unified_Modeling_Language_tools

UML with C++ code generator
x

https://umbrello.kde.org/installation.php



Free UML BOOKS
http://www.freebookcentre.net/Language/Free-Uml-Books-Download.html

CS teaching resource

https://csta.acm.org/Curriculum/sub/CurrResources.html

QUBEHUB software for simulations

Including RStudio, XPPAUT, PPLane etc.

https://qubeshub.org/resources/software

references for 2-credits bioinformatics course

Genomics Medicine Gets Personal, EdX
https://courses.edx.org/courses/course-v1:GeorgetownX+MEDX202-01+2015_3T/courseware/83df4b53f2d444a38a90558b5c639711/aa544225cd604b689f7e421c90a624fe/

https://www.coursera.org/courses/?query=bioinformatics
https://www.coursera.org/specializations/bioinformatics

Introduction to Bioinformatics 4th Edition, Arthur Lesk

Bioinformatics for biologists, 

http://www.amazon.com/Bioinformatics-Biologists-Pavel-Pevzner/dp/1107648874/ref=sr_1_8?s=books&ie=UTF8&qid=1443631856&sr=1-8&keywords=bioinformatics&refinements=p_n_feature_nine_browse-bin%3A3291437011%2Cp_72%3A1250221011

Educational kits

http://ice.chem.wisc.edu/Catalog/SciKits.html

sliderule: foundations of data science

foundations of data science by Claudia Gold
https://www.mysliderule.com/learning-paths/data-analysis/learn/?

R related teach resources for BIO386

EdX computational genomics using R
http://genomicsclass.github.io/book/pages/classes.html

R programming by microsoft
https://www.edx.org/course/introduction-r-programming-microsoft-dat204x?utm_source=Course%20Announcements%20Mailing%20List&utm_medium=email&utm_content=image&utm_campaign=Student_Newsletter_August_4

Data Carpentry
https://github.com/datacarpentry/R-genomics
https://github.com/QinLab/r-bio.github.io

homo sapiens migration

https://www.facebook.com/businessinsider/videos/vb.20446254070/10152823614039071/?type=2&theater

College Learning Assessment

http://en.wikipedia.org/wiki/Collegiate_Learning_Assessment#Criticisms

http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.134.383&rep=rep1&type=pdf&utm_source=buffer&utm_campaign=Buffer&utm_content=buffer5a240&utm_medium=twitter

Online books, PDE, ODE

http://jerryfarlow.com/ode-books-online/

Video of research talks at NIH

http://videocast.nih.gov/PastEvents.asp

useful teaching materials

Farmington aging study
http://videocast.nih.gov/Summary.asp?File=18760&bhcp=1

NIH interest groups
http://www.nih.gov/sigs/

scientific cartoon

=> pentagon glucose on polarity of DNA strand.  Glucose said, "I am the decider."

=> electron transport chain, dam, and power

data analysis cartoon
http://stats.stackexchange.com/questions/423/what-is-your-favorite-data-analysis-cartoon

CURE survey

Instructor's form

Student forms

Molecular classification of cancer is more informative than locations

http://www.newsweek.com/its-time-us-think-about-cancer-differently-263466