Coder Social home page Coder Social logo

mingchen4 / csb Goto Github PK

View Code? Open in Web Editor NEW

This project forked from csb-book/csb

0.0 1.0 0.0 26.69 MB

Material for Computing Skills for Biologists

License: GNU General Public License v3.0

R 4.44% Shell 4.18% Python 0.69% Jupyter Notebook 64.75% TeX 25.93%

csb's Introduction

CSB

Git repository accompanying the book:

Computing Skills for Biologists --- A Toolbox by Stefano Allesina & Madlen Wilmes, Princeton University Press, 2019.

See also the website computingskillsforbiologists.com for news, errata, and extra material.

How to download the material:

Install Git

To download all the material, you first need to install Git. The instructions are here.

Once you have installed Git, open a Terminal:

Linux Ubuntu

Press Ctrl + Alt + T or open the dashboard and type terminal.

Mac OSX

The application Terminal is located in Utilities within Applications.

Windows

When you install Git, the program GitBash is installed automatically. Open GitBash.

Clone the repository

The terminal should open in your home folder. Type

git clone https://github.com/CSB-book/CSB.git

The command downloads all the material on your computer. To make sure you everything went well, type:

ls CSB/

If you see a list of directories, everything is good. You can close the terminal.

Organization of the material

For each of the chapters, we provide a directory containing:

  • installation: instructions on how to install the software.
  • data: the data used for example and exercises; for each data set, see the about file for a reference to the original article and a link to the Dryad record.
  • sandbox: where you should be working.
  • solutions: contains the solution to the exercises at the end of each chapter. A full solution is provided in the appropriate language (e.g., Python, R, SQL), as well as a pdf file. A markdown file contains the description of the solution in plain English: if you are stuck on an exercise, check this file out first, and get inspired to solve the problem.

Acknowledgements

Much of the data used for the exercises and examples was published through the Dryad Digital Repository. We want to thank all the scientists who made their data available without restrictions. For each data set, a citation for the original paper and a link to the Dryad record are provided.

Contacts

For any question, or to signal a bug, typo, etc. please contact us at [email protected]

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.