/2018-03-06-ibioic

Teaching materials for 6-7th March 2018 delivery of introductory bioinformatics training course for IBioIC.

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JHI/IBioIC Introduction to Bioinformatics: 6-7 March 2018

Introduction

Welcome to the GitHub repository for the JHI/IBioIC Introduction to Bioinformatics course. This document provides a schedule for this course presentation, and links to course documentation and setup.


Setup

To participate in this workshop, you will need access to some standard bioinformatics software packages, listed below. In addition, you will need an up-to-date web browser. Installation and configuration instructions for these tools, and the course materials, are provided at the site linked below:

Prerequisites

To use the course materials with your own laptop, you will require:

If there are installation issues, or it is otherwise not possible to install the prerequisites, we provide a virtual machine image with all the tools and materials pre-installed. For this you will require:

This virtual machine is large (>11GB) so if you need to download it we strongly advise that you do so before attending the course.


Schedule: 6th-7th March 2018, University of Strathclyde, Glasgow

Location: Room CU330B, Curran Building, University of Strathclyde, Cathedral Street, Glasgow.

Day 1: 6th March 2018

09:30 1. Welcome and introduction (Leighton, Sue, Peter)
2. Introduction to Bash, Jupyter and Python (Peter)
3. Introduction to sequence data and bioinformatics (Peter)
12:30 Lunch break
13:30 Mining bioinformatics databases (Leighton)
16:30 Wrap-up
17:00 END

Day 2: 7th March 2018

09:30 1. Reproducible research (Leighton)
2. Worked example (Peter, Leighton, Sue)
12:30 Lunch break
13:30 Structural bioinformatics (Sue)
16:30 Wrap-up
17:00 END

Previous presentations

  • 16th-17th March 2017: University of Strathclyde, Glasgow (website)

Course materials

We provide the course notebooks and slides as webpages, in the links below:

Slidesets

0. Introducing the Software Platform

Lessons

Learning Outcomes

  • Familiarity with the Linux command line
  • Familiarity with remote access to a Linux server
  • Familiarity with Jupyter notebooks
  • Familiarity with Python
  • Awareness of counting from zero versus from one

1. Sequences

Lessons

Learning Outcomes

  • Familiarity with FASTA file format
  • Familiarity with GenBank file format
  • Familiarity with Artemis for viewing GenBank files
  • Familiarity with Jalview for viewing multiple sequence alignments

2. Mining Public Databases

Lessons

Slidesets

Learning Outcomes

  • Programmatic control of common bioinformatics tools
  • Programmatic querying of online bioinformatics resources
  • Analysis of bioinformatics tool output with pandas
  • Visualisation of bioinformatics tool output with biopython and seaborn
  • Interpretation of bioinformatics tool output

3. Worked Example

Slidesets

Lessons

4. Structural Bioinformatics

Lessons

Learning Outcomes

  • Obtaining representative structures from public databases
  • Visualisation and interpretation of protein structure
  • Scripting structure visualisation tools to generate images for publication
  • Comparison of protein structures to make functional inferences
  • Predicting protein structure from sequence

About the authors and tutors