Unit information: Introduction to Bioinformatics in 2025/26

Unit name	Introduction to Bioinformatics
Unit code	BIOLM0051
Credit points	20
Level of study	M/7
Teaching block(s)	Teaching Block 1 (weeks 1 - 12)
Unit director	Professor. Pisani
Open unit status	Not open
Units you must take before you take this one (pre-requisite units)	None
Units you must take alongside this one (co-requisite units)	None
Units you may not take alongside this one	None
School/department	School of Biological Sciences
Faculty	Faculty of Life Sciences

Unit Information

Why is this unit important?

Students come to our course with a broad range of backgrounds, from biology to computer science and everywhere in between. The unit will help you develop basic bioinformatics skills, including how to use computers, command line interfaces, Unix-based operating systems (the main platform for bioinformatics), and high-performance computing. It will also provide a beginner-level introduction to programming in the context of biological data analysis – for example, using Python to automate simple sequence analysis tasks. You will be taught fundamental skills in the context of real-world bioinformatics challenges, such as interacting with databases, finding relevant data, and applying skills to test biological hypotheses.

How does this unit fit into your programme of study?

The purpose of this unit is to help you develop (or refresh) a basic foundation in core bioinformatics skills, and to provide a common toolkit upon which subsequent units in the course can build. The skills learned here will provide the basis for more advanced sequence analysis tasks such as genome assembly and gene expression analysis in TB2 units.

Your learning on this unit

An overview of content

The unit covers three main strands of activity, which are interleaved throughout the course to maintain variety and interest.

1. Computing skills for bioinformatics. You will learn how computers work, about different operating systems, and be trained in the use of Unix-based and command line interfaces. You will learn how to log into remote systems – in the cloud and on HPC – and how to run and automate analyses on these compute resources.
2. Introductory programming for analysis of biological data. You will be introduced to the logic of programming through training in Python, a general purpose and widely used language in biology and, more broadly, in data science. You will learn how to write simple Python scripts to make analysis of biological data easier, quicker, more reproducible and more reliable.
3. Introduction to applied bioinformatics. Through a series of applied problems and challenges of the kinds that bioinformaticians routinely face, you will learn how to use your computational and programming skills to do biology. Topics will include using online databases to make predictions about sequence functions, reconstructing evolutionary trees, and identifying unknown organisms from environmental DNA.

How will students, personally, be different as a result of the unit

Students will develop an understanding of how computers work, the the skills needed to work as bioinformaticians in research labs (for example, for the research project in TB2), the ways of thinking needed to write effective code, and the confidence that they are able to do biology using computational approaches.

Learning outcomes

1. To describe the component parts of computers, and to understand how cloud and HPC computing works.
2. To use command line interfaces to carry out basic tasks on a computer.
3. To design and write Python code to perform simple bioinformatics analyses.
4. To apply bioinformatics tools such as BLAST to identify and characterise biological sequences.

How you will learn

The primary mode of learning in this unit is active, problem-based learning: lecturers will introduce the ideas and theory underpinning a concept, then lead a practical class in which you will work on computer-based tasks (on your own laptop, or course-supplied laptop) designed to help you develop the target skills. This mode of learning is highly appropriate for bioinformatics training, because this is fundamentally a practical and applied discipline: bioinformatics is a set of tools (and an approach) to doing biology using computers.

These tasks will include:

1. Problem-based worksheets, asking you to answer questions or solve simple problems by working through exercises on the computer (for example: navigate to a directory; inspect the contents of a file).
2. Programming challenges, in which you will be asked to write Python code to carry out simple analyses appropriate to the introductory nature of the unit (for example: count the number of sequences in a file, or the size of a genome).
3. Data analysis challenges, in which you will be given a small sequence dataset and asked to answer some questions about it using the bioinformatics skills you are developing.

How you will be assessed

Tasks which help you learn and prepare you for summative tasks (formative)

• Introductory use of the bash command line (tasks such as changing directory, reading and writing text files, and connecting to remote computers), guided via practical sheets.
• Basic bash and Python scripting tasks involving simple analyses of sequence data (motif finding), looping over files, and parallelizing jobs on a multicore processor architecture.
• Interactive use of various commonly used online bioinformatics databases, such as the BLAST interface at NCBI and EBI.

Tasks which count towards your unit mark (summative)

A piece of coursework involving a short analysis pipeline (100%). The task will directly use the skills developed formatively, and will require combining several different tools together to analyse a small dataset of biological sequences, and then interpreting the results.

When assessment does not go to plan

The summative assessment is an individual assignment, so if you are unable to submit due to extenuating circumstances or fail to pass at the first attempt, you may be allowed to carry out the analyses on a new dataset and resubmit with an agreed revised deadline.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. BIOLM0051).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the University Workload statement relating to this unit for more information.

Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates within the Regulations and Code of Practice for Taught Programmes.