Appendix #: Catalog of Jupyter Notebooks

This page catalogs all of the existing interactive Jupyter notebook content currently offered by the EMBRIO institute. See the descriptions in each section for more information.

Instructional Modules

These notebooks are full educational modules for learning the basics of computational biology.

How to Use Jupyter Notebooks (in Google Colab)

Description: This notebook will walk you through the basics of using interactive Jupyter notebooks within the Google Collaboratory environment. If you are not experienced in using Jupyter or other coding notebook interfaces, it is highly recommended that you walk through this notebook before doing anything else. Google Chrome is recommended for best performance.

Link to notebook: Using Google Colabs

Recommended Prerequisites:

• None

Introduction to Scientific Computing: Parts 1–3

Description: This three part module series will teach you the basics of coding in Python, as well as how to set up functions, import data,

Learning Objectives:

• Basics of Python syntax (printing, mathematical operations)

• Mathematical operations

• Data types and variables

• Plotting and data visualization

• Loops, if/else statements, and other control flow

• Defining functions

Link to notebooks:

• Scientific Computing Part 1: Defining Variables and Plotting

• Scientific Computing Part 2: For Loops and Control Flow

• Scientific Computing Part 3: Defining Functions

Recommended Prerequisites:

• How to Use Jupyter Notebooks

Projects

These notebooks are sample projects presented as Colab notebooks. Work through these to test your skills!

Reaction and Diffusion in an Antibody Detection Device

Description

You have been commissioned by a biotech company to define the operating procedures for their serological test. Specifically, you need to develop a computational model of their detector and use this model to determine: (1) What is the limit of detection of their device (i.e., what is the lowest concentration of patient antibody that this device can detect) and (2) How long after loading a sample should you wait before reading the result? The tasks in this project walk you through the steps toward answering these questions.

Learning Objectives:

Link to notebook: Antibody Detection Project

Recommended Prerequisites:

• How to Use Jupyter Notebooks

• Introduction to Scientific Computing

Example Papers

These notebooks summarize published papers that utilize computational methods to address biological problems and questions. Models from the papers have been converted to interactive Python code for many of these papers.

Morphogen Gradients

Description

Morphogen gradients have been observed in tissue and are believed to be the driving force behind patterns of cells and tissues. Generaly these morphogens are produced from a localized source and are moved around to form a gradient among surrounding tissues, however the mechanism behind the formation of these stable gradients is something of a controversey.

Learning Objectives

Link to Notebook: Morphogen Gradients

Recommended Prerequisites:

• None