Designing a course model for distance-based online bioinformatics training in Africa: The H3ABioNet experience

Africa is not unique in its need for basic bioinformatics training for individuals from a diverse range of academic backgrounds. However, particular logistical challenges in Africa, most notably access to bioinformatics expertise and internet stability, must be addressed in order to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics Network for H3Africa, has therefore developed an innovative, free-of-charge “Introduction to Bioinformatics” course, taking these challenges into account as part of its educational efforts to provide on-site training and develop local expertise inside its network. A multiple-delivery–mode learning model was selected for this 3-month course in order to increase access to (mostly) African, expert bioinformatics trainers. The content of the course was developed to include a range of fundamental bioinformatics topics at the introductory level. For the first iteration of the course (2016), classrooms with a total of 364 enrolled participants were hosted at 20 institutions across 10 African countries. To ensure that classroom success did not depend on stable internet, trainers pre-recorded their lectures, and classrooms downloaded and watched these locally during biweekly contact sessions. The trainers were available via video conferencing to take questions during contact sessions, as well as via online “question and discussion” forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted to other settings.


Module Name: Introduction to bioinformatics and bioinformatics resources and databases
Final resources for the 2016 version of this module can be found here: http://training.h3abionet.org/IBT_2016/?page_id=30

Prerequisites
• Basic background in molecular biology • Basic use of an internet browser

Curriculum Session 1: What is Bioinformatics and why is it important?
Learning objectives and outcomes  Provide an introduction to what bioinformatics is and why it is important  Provide an overview of the application areas of bioinformatics, with a focus on the topics that will be taught in the course  Explain what type of knowledge will be gained from the course

Session 2: Biological databases and resources (NCBI, EBI)
Learning objectives: • Describe how bioinformatics data is stored and organised • Describe the different types of data found at the NCBI and EBI resources • Explain how to locate and extract data from key bioinformatics databases and resources Learning outcomes: • Locate and use the main databases at the NCBI and EBI resources • Know the difference between databases, tools, repositories and be able to use each one to extract specific information • Extract data from specific databases using accessions numbers, gene names etc.
• Use selected tools at NCBI and EBI to run simple analyses on genomic sequences • Explain the concept of files and how they are created in Linux • Describe how to extract data from files using grep, cut, sort, uniq and output redirection

Learning outcomes:
• Be able to create and edit files using a text editor nano • Be able to search through a file for a matching string or regular expression using grep • Be able to use common commands such as cut, sort, uniq • Be able to redirect the output of a command to a file Session 3: Permissions, groups, and process control Learning objectives: • Explain file and directory permissions and how to change them • Explain loops, variables and script generation to automate tasks • Explain environment variables and why they are important • Learn how to ssh onto a remote machine • Provide an outline of the different approaches to sequence alignmentexhaustive vs. heuristic Learning outcomes: • Extract and generate pairwise sequence alignments for a protein sequence of interest • Describe and interpret the metrics used to assess the quality of a pairwise sequence alignment, identity versus similarity • Describe the differences between homologues, paralogues and orthologues • Use a pairwise sequence approach to identify mutations between two sequences

Session 2: Pairwise sequence alignment
Learning objectives: • Define the differences between global and local pairwise alignment algorithms • Outline the basic principles of pairwise alignments, scoring matrices and gap penalties • Describe the concept of the dynamic programming approach for pairwise sequence alignment (global and local) Learning outcomes: • Align two sets of sequences using both a global and local alignment approach • Explain the effect of changing parameters such as scoring matrices, gap penalties etc. • Interpret the output of a pairwise alignment and when the global or local alignment method is more appropriate to use