2018-03-06-ibioic
Teaching materials for 6-7th March 2018 delivery of introductory bioinformatics training course for IBioIC.
JHI/IBioIC Introduction to Bioinformatics: 6-7 March 2018
- Introduction
- Setup
- Schedule: 6th-7th March 2018, University of Strathclyde, Glasgow
- Previous presentations
- Course materials
- About the authors and tutors
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:
- An up-to-date web browser (Chrome, Firefox, Safari, etc.)
- Anaconda (this provides Python and Jupyter) homepage
- Artemis homepage
- Bash (for Windows, Git Bash) Git Bash homepage
- Blast homepage
- Git (provided with Git Bash on Windows) Git for Windows homepage
- Jalview homepage
- JMol homepage
- Muscle homepage
- Python packages:
biopython,bioservices,seaborn
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
- Course schedule
0. Introducing the Software Platform
Lessons
- 00. The command line and Linux (
terminal) - introductory - 01. Jupyter Notebooks (
notebook) - introductory - 02. Python (
notebook) - introductory
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
- 01. FASTA format and parsing it (
notebook) - introductory - 02. GenBank format and annotation (
browser,notebook) - introductory - 03. Parsing GenBank (
notebook) - intermediate - 04. Multiple Sequence Alignment (
terminal) - introductory
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
- 01.
BLAST+at NCBI (browser) - introductory - 02.
BLAST+at the terminal (terminal) - introductory - 03. Programming for local
BLASTsearches (notebook) - intermediate - 04. Using NCBI
BLAST+service with Python (notebook) - intermediate - 05. Reciprocal
BLASTHits (RBH) (notebook) - advanced - 06.
UniProt(browser) - introductory - 07. Programming for
UniProt(notebook) - intermediate - 08.
KEGG(browser) - introductory - 09. Programming for
KEGG(notebook) - intermediate - 10.
Ensembl(browser) - introductory
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
biopythonandseaborn - Interpretation of bioinformatics tool output
3. Worked Example
Slidesets
Lessons
-
00. Challenge (
notebook/browser) - introductory/intermediate -
lipase_investigation.ipynb- the notebook developed during the class
4. Structural Bioinformatics
Lessons
- 01. RCSB (
browser) - introductory - 02. Web-based visualisation (
browser) - introductory - 03. JMol visualisation (
terminal) - intermediate - 04. Structure comparisons (
browser) - introductory - 05. Structure prediction (
browser) - introductory
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
- Peter Cock is a computational biologist at the James Hutton Institute, and lead developer for Biopython. He works largely with nematodes and viruses.
- Sue Jones is a computational biologist at the James Hutton Institute, with interests in functional genomics, transcriptional regulation, and viruses.
- Leighton Pritchard is a computational biologist at the James Hutton Institute, with particular interests in host-microbe interactions, and systems and synthetic biology.