README.md

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

• Introduction
• Setup
  • Prerequisites
• Schedule: 6th-7th March 2018, University of Strathclyde, Glasgow
• Previous presentations
• Course materials
  • 0. Introducing the Software Platform
  • 1. Sequences
  • 2. Mining Public Databases
  • 3. Worked Example
  • 4. Structural Bioinformatics
• 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.

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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:

• Setup instructions for the workshop

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:

• The virtual machine image download
• VirtualBox homepage

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

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

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

• Map

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)

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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 BLAST searches (notebook) - intermediate
• 04. Using NCBI BLAST+ service with Python (notebook) - intermediate
• 05. Reciprocal BLAST Hits (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 ​

• Interpreting BLAST results ​

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 ​

• Reproducible research

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

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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.