Life sciences and technology are an integral part of the global economy. Our Bioinformatics MSc has been designed with input from major industry players to meet the current and emerging skill gaps for professional bioinformaticians.
Introduction
This course will equip you with the background in biology, statistical analysis, and computing skills necessary to work with modern biological data from genomic, proteomic and metabolomic studies.
You’ll be trained with an emphasis on hands-on practical experience, so that you can tackle your research project with confidence.
If Bioinformatics is your passion, you may wish to continue your education by studying a PhD following successful completion of this MSc.
Please note that this programme is suitable for intercalating medical students.
Who is this course for?
This master’s course is for graduates from a Biological Sciences background who want to combine the skills and technologies from computer science and biology to help better understand and interpret biological data.
What you'll learn
The knowledge and skills necessary to perform bioinformatics analyses
Statistical techniques in the design of experiments in biological research
Theoretical and technical knowledge in sequence analysis, phylogenetics, and the modelling of proteins, and others
Coding skills to perform tasks in the biological sciences
How to analyse and interpret complex genomic data sets
The understanding of proteomic and metabolomic techniques and related data analysis
Course content
Discover what you'll learn, what you'll study, and how you'll be taught and assessed.
If you're able to study part-time, you'll
study the same modules as the full-time master's degree over a longer period, usually 24 months. You
can make studying work for you by arranging your personal schedule
around lectures and seminars which take place during the day. After you
complete all the taught modules, you will complete your final
dissertation or project and will celebrate your achievements
at graduation the following term.
Studying part-time means you can study alongside work or any
other life commitments. You will
study the same modules as the full-time master's degree over a longer period, usually 24 months. You
can make studying work for you by arranging your personal schedule
around lectures and seminars which take place during the day. After you
complete all the taught modules, you will complete your final
dissertation or project and will celebrate your achievements
at graduation the following term.
Semester one
Compulsory modules
Practical Bioinformatics (LIFE748)
Credits: 30 /
Semester: whole session
The aim of this module is to develop knowledge and skills necessary to perform bioinformatics analyses, in order to prepare students for future bioinformatics work, either inside or outside an educational setting. The student will: (i) get hands on experience with genomic and protein data (genome sequence, annotation and analysis), and thus a solid grounding in practical bioinformatics work, and (ii) meet with their project supervisor, to prepare for their MSc project work.
The module will be taught through a combination of lectures, tutorials, and workshops. The topics covered will be introduced with a lecture, and then we will apply the lecture material to real-world practical data sets in workshops. The module will be assessed via three coursework assessments, including a presentation, a scientific report and a research project plan.
ADVANCED STATISTICS FOR BIOLOGICAL RESEARCH (LIFE707)
Credits: 15 /
Semester: semester 1
Successful research in the biological sciences inevitably depends on the power that statistical inference provides for hypothesis testing. Understanding which test to use and when is the key to success. This module aims to further this understanding of, and competence in, the use of statistical techniques in the design of experiments in biological research, and in the analysis and interpretation of data.
The module is available to students who are on-campus (LIFE707) or, alternatively, who are studying on a University of Liverpool programme while off-campus (LIFE607), for example in a yearly placement in industry or while studying at an overseas University.
The learning and teaching materials are delivered as an online set of resources (available through Canvas). The module aims to provide a guide to the statistics that students will need to complete an advanced research project (M-level or PhD), and the ability to develop a research-level statistical approach to the analysis of biological data. The module will also introduce students to the powerful open access statistical software package, R.
INFORMATICS FOR LIFE SCIENCES (LIFE721)
Credits: 15 /
Semester: semester 1
Bioinformatics is a key skill needed in many research settings. This module gives students a theoretical and technical grounding in a range of application areas including bioinformatics-related topics such as sequence analysis, phylogenetics, and the modelling of proteins, and others. While lectures are provided on core topics, there is a strong emphasis on practical exercises to demonstrate the application of common tools and data sources in these contexts. Teaching is delivered in the form of a weekly lecture and workshops. Students will be given guided reading and online activities to support their learning. The module will be assessed by three data analysis continuous assessments.
CODING FOR LIFE SCIENCES (LIFE733)
Credits: 15 /
Semester: semester 1
This module is aimed at postgraduate students in the Life Sciences, wishing to learn about methods for use in data-intensive research. The module provides a broad introduction to the use of Python coding for performing basic tasks in the biological sciences. The student will get practical experience in writing their own Python scripts for basic bioinformatics tasks, such as manipulating DNA, RNA and protein sequences, file input/output and working with other programs, such as BLAST. There is also an introduction to data visualisation using Python, and simple techniques used in data science, including a basic introduction to machine learning.
Around 10 hours of lectures will be provided on core topics, with a strong emphasis on practical activity in workshops and tutorials (totalling around 40 hours), allowing students to gain confidence in writing scripts for their own tasks. The module will be assessed by two short coding assignments, one team working coding assignment building a bioinformatics pipeline, and a data science mini-project.
Programme details and modules listed are illustrative only and subject to change.
Semester two
Compulsory modules
Practical Bioinformatics (LIFE748)
Credits: 30 /
Semester: whole session
The aim of this module is to develop knowledge and skills necessary to perform bioinformatics analyses, in order to prepare students for future bioinformatics work, either inside or outside an educational setting. The student will: (i) get hands on experience with genomic and protein data (genome sequence, annotation and analysis), and thus a solid grounding in practical bioinformatics work, and (ii) meet with their project supervisor, to prepare for their MSc project work.
The module will be taught through a combination of lectures, tutorials, and workshops. The topics covered will be introduced with a lecture, and then we will apply the lecture material to real-world practical data sets in workshops. The module will be assessed via three coursework assessments, including a presentation, a scientific report and a research project plan.
Advanced Genomic Analysis (LIFE750)
Credits: 15 /
Semester: semester 2
Modern biology and medicine are increasingly making use of complex genomic data sets. As a result, there is increasing demand for graduates who can analyse and interpret these data.
In this module, you will learn the fundamentals of a broad range of genomic analyses. You will learn how and when to apply different genomic technologies, and how to analyse the data– to understand fundamental biological processes, to reconstruct the history of organisms and to trace disease outbreaks, for example.
You will be taught through a combination of lectures, to give a strong grounding in each topic– followed by hands on workshops– where you will gain experience in applying your skills to data analysis. Most topics will be covered in two-week sessions, with a typical week consisting of two-hours of contact time.
To demonstrate your mastery of the topics, you will engage in a set of assessments that mirror real-world applications of your knowledge: a poster presentation (30%) on an advanced topic in genomic analysis, and a synthetic report (70%) that applies the material covered to a novel biological context.
We have developed this module, along with all other modules in this Programme, in consultation with partners from both industry and academia, in order to ensure that graduates have skills that are currently in demand.
Computational Biology (LIFE752)
Credits: 15 /
Semester: semester 2
With the advent of genomics and functional genomics, biology has become a quantitative data-rich discipline. This has created unprecedented opportunities in virtually every area of life sciences. With the right tools, it is now possible to address fundamentally important biological questions simply analysing already available datasets. This module is designed to prepare students for this very challenge. The module covers the most important aspects of computational biology. These range from the analysis of large datasets to infer biological mechanisms to the use of mathematical modelling to conceptualize and simulate complex biological phenomena. In addition to providing an intuitive overview of the basic theoretical principles, the module will focus on real life applications through multiple cases studies. Among these, students will learn how to identify drug targets and mechanisms of drug resistance and how to understand mathematical models of biological systems. They will then learn aspects of quantitative system pharmacology and physiologically based pharmacokinetic modelling pharmacokinetic/pharmacodynamic modelling.
The module will be taught through a combination of lectures, workshops and seminars. The module will be assessed via a written a report and a literature critique.
Proteomics Metabolomics and Data Analysis (LIFE754)
Credits: 15 /
Semester: semester 2
Proteomics and metabolomics represent powerful tools towards unbiased, quantitative and high-throughput analysis of biological systems. Rapid “omic” technological developments in the post‐genomic era have provided insights into protein structures, biosynthesis and interactions, as well as the complex metabolic processes that are of significant importance in biological and medical research. The aims of this course are to provide a comprehensive understanding of proteomic and metabolomic techniques and related data analysis, and to illustrate how they can be applied in fundamental biological research and industrial applications. The module will be taught by lectures and workshops. The module will be assessed via two a scientific reports.
Programme details and modules listed are illustrative only and subject to change.
Final project
Compulsory modules
MSC RESEARCH PROJECT (LIFE703)
Credits: 60 /
Semester: summer
In this module students will work on a research project in their chosen area of study under the supervision of a project supervisor. Students are expected to work independently, with guidance provided by their supervisor. Students will create a plan of work at the start of the project, and will present their work orally, as well as write a final project report. Students will also be assessed on their approach and technique during the project. Students will defend their work in a viva at the end of the module. This module will give students experience in conducting their own independent research project, and the presentation of this work through oral and written formats.
Programme details and modules listed are illustrative only and subject to change.
How you'll learn
You will experience a range of teaching and learning methods, including lectures, seminars, workshops, group discussion and e-learning.
Programme modules encourage individual and group work where you will tackle problems by developing ideas and hypotheses, design learning strategies to solve problems, and then analyse and interpret your findings.
Course material is available 24-hours a day on Canvas, our online learning platform. One-to-one meetings with your research supervisor will allow you to discuss science, develop your critical thinking and creativity through an ongoing feedback model.
Your master research project provides a full academic research experience, including the planning, execution and communication of scientific research.
How you're assessed
Assessment of knowledge and understanding, practical skills and transferrable skills is through a blended mix of coursework that may include practical and project reports, essays, completion of workbooks, talks, data handling sessions and posters.
All modules will provide you with feedback on your learning progress and allow for adjustment of your learning. Electronic resources available on the University virtual learning environment support learning and teaching.
Liverpool Hallmarks
We have a distinctive approach to education, the Liverpool Curriculum Framework, which focuses on research-connected teaching, active learning, and authentic assessment to ensure our students graduate as digitally fluent and confident global citizens.
Course options
Studying with us means you can tailor your degree to suit you. Here's what is available on this course.
As a Bioinformatics student, you will benefit from the School of Life Sciences experience in delivering dynamic, world-class, inspirational research-led teaching. We are a melting-pot for the study of the biological sciences, and have been for over 140 years.
Support for students with differing needs from the Disability advice and guidance team. They can identify and recommend appropriate support provisions for you.
An exciting place for postrgradute study
Programmes taught by internationally-renowned scientists and clinicians
Research-connected education covering the full life science spectrum from biochemistry to zoology
Access to world-class facilities
Provide specialist training with taught and research components
Graduates with a Bioinformatics MSc are highly sought after. In the public sector, bioinformaticians are in demand in research institutes, government departments, the Health Service, forensic science and the Environment Agency.
Commercial sectors such as the pharmaceutical, biotechnology and agriculture industries are also employers of our graduates, especially with the increase of next-generation sequencing and the corresponding data analysis that is required.
There is also a current demand for science teachers and following the completion of a PGCE, this master’s is suitable for those interested in a career in teaching. In fact, many of our graduates pursue careers in a wide range of fields, including management, where the skills obtained through this degree are of considerable benefit.
Career support from day one to graduation and beyond
The MSc Bioinformatics prepares you for a diversity of job opportunities in the public and private sector. Potential career pathways include, but are not limited to, the roles of:
Bioinformatics Scientist
Research Scientist
Biostatistician
Bioinformatician
Molecular Biologist
Microbiologist.
Fees and funding
Your tuition fees, funding your studies, and other costs to consider.
Tuition fees
UK fees (applies to Channel Islands, Isle of Man and Republic of Ireland)
Full-time place, per year
£11,900
Part-time place, per year
£5,950
International fees
Full-time place, per year
£24,750
Part-time place, per year
£12,375
Fees stated are for the 2023-24 academic year.
Tuition fees cover the cost of your teaching and assessment, operating facilities such as libraries, IT equipment, and access to academic and personal support.
We understand that budgeting for your time at university is important, and we want to make sure you understand any course-related costs that are not covered by your tuition fee. This could include buying a laptop, books, or stationery.
Normally, at least a 2.1 Honours degree in a Biological Sciences subject or equivalent, including at least one module providing training in statistics. Candidates must have a scientific background acceptable to the Director of the programme.
International qualifications
If you hold a bachelor’s degree or equivalent, but don’t meet our entry requirements, a Pre-Master’s can help you gain a place. This specialist preparation course for postgraduate study is offered on campus at the University of Liverpool International College, in partnership with Kaplan International Pathways. Although there’s no direct Pre-Master’s route to this MSc, completing a Pre-Master’s pathway can guarantee you a place on many other postgraduate courses at The University of Liverpool.
Liverpool bursts with diversity and creativity which makes it ideal for you to undertake your postgraduate studies and access various opportunities for you and your family.
To fully immerse yourself in the university experience living in halls will keep you close to campus where you can always meet new people. Find your home away from home.
Discover what expenses are covered by the cost of your tuition fees and other finance-related information you may need regarding your studies at Liverpool.
Contact us
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