Course details
- Entry requirements: A 2:1 Honours degree
- Full-time: 12 months
- Part-time: 24 months
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Biosciences 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.
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.
You will be taught by internationally renowned scientists at a University with internationally excellent Research Centres, including the University of Liverpool Computational Biology Facility, the newly established Centre for Metabolomics, the Centre for Proteomics, and the Centre for Genomic Research.
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.
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.
Discover what you'll learn, what you'll study, and how you'll be taught and assessed.
The aim of this module is to encourage students to develop the necessary knowledge and skills in core and advanced bioinformatics analyses to prepare students for bioinformatics related careers, either inside or outside an academic setting. Aligned to emerging advances in the bioinformatics field, the student will: (i) gain experience of core e.g., genome assembly and advanced e.g., machine learning applied bioinformatics techniques, with examples drawn from widely used genomic and protein data and thus, develop a solid grounding in practical bioinformatics work; (ii) develop the necessary soft skills to effectively communicate, problem manage, and critically evaluate scientific hypotheses and (iii) acquire the necessary knowledge and technical skills, under the personal guidance of a research project supervisor to deliver an original piece of bioinformatics research.
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 poster.
Data skills are essential for a career in modern biology. Biological studies increasingly involve the generation of large or complex sets of data, and the ability to analyse data is a core component of a successful biologist’s skill set. Digital fluency is also required more widely outside biological research and a grounding in data analysis is in demand by a broad range of employers. Here you will learn the ability to visualise data, critically test hypotheses, and to interpret and present results.
The learning and teaching materials are delivered as an online set of resources (available through Canvas) coupled with computer-based practical workshops. The module will also introduce students to the powerful open access statistical software package, R.
The module will be assessed by a written data analysis report and an open-book exam
For any students studying off-campus – due to a placement in industry or studying at an overseas University – on-line drop-in sessions will be provided instead of the practical workshops.
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 two coursework assessments. The assessments will allow students to demonstrate their understanding of the tools used in workshops and interpretation of results.
This module is aimed at postgraduate students in the Biosciences, 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.
Around 10 hours of lectures will be provided on core topics, with a strong emphasis on practical activity in workshops (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.
The aim of this module is to encourage students to develop the necessary knowledge and skills in core and advanced bioinformatics analyses to prepare students for bioinformatics related careers, either inside or outside an academic setting. Aligned to emerging advances in the bioinformatics field, the student will: (i) gain experience of core e.g., genome assembly and advanced e.g., machine learning applied bioinformatics techniques, with examples drawn from widely used genomic and protein data and thus, develop a solid grounding in practical bioinformatics work; (ii) develop the necessary soft skills to effectively communicate, problem manage, and critically evaluate scientific hypotheses and (iii) acquire the necessary knowledge and technical skills, under the personal guidance of a research project supervisor to deliver an original piece of bioinformatics research.
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 poster.
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.
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 two written reports.
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.
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.
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.
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.
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.
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 Biosciences 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.
From arrival to alumni, we’re with you all the way:
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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.
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:
Your tuition fees, funding your studies, and other costs to consider.
UK fees (applies to Channel Islands, Isle of Man and Republic of Ireland) | |
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Full-time place, per year | £13,300 |
Part-time place, per year | £6,650 |
International fees | |
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Full-time place, per year | £28,300 |
Part-time place, per year | £14,150 |
Tuition fees cover the cost of your teaching and assessment, operating facilities such as libraries, IT equipment, and access to academic and personal support.
If you're a UK national, or have settled status in the UK, you may be eligible to apply for a Postgraduate Loan worth up to £12,167 to help with course fees and living costs. Learn more about fees and funding.
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.
Find out more about the additional study costs that may apply to this course.
We offer a range of scholarships and bursaries that could help pay your tuition and living expenses.
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The qualifications and exam results you'll need to apply for this course.
We've set the country or region your qualifications are from as United Kingdom. Change it here
Your qualification | Requirements |
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Postgraduate entry requirements |
We accept a 2:2 honours degree from a UK university, or an equivalent academic qualification from a similar non-UK institution. This degree should be in a Biological Sciences subject or equivalent, including at least one module providing training in statistics, or a degree from a Science and Engineering subject, with a demonstrated interest or modules in Biology. 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. |
You'll need to demonstrate competence in the use of English language, unless you’re from a majority English speaking country.
We accept a variety of international language tests and country-specific qualifications.
International applicants who do not meet the minimum required standard of English language can complete one of our Pre-Sessional English courses to achieve the required level.
English language qualification | Requirements |
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IELTS | 6.5 overall, with no component below 6.0 |
TOEFL iBT | 88 overall, with minimum scores of listening 19, writing 19, reading 19 and speaking 20. TOEFL Home Edition not accepted. |
Duolingo English Test | 120 overall, with no component below 105 |
Pearson PTE Academic | 61 overall, with no component below 59 |
LanguageCert Academic | 70 overall, with no skill below 65 |
PSI Skills for English | B2 Pass with Merit in all bands |
INDIA Standard XII | National Curriculum (CBSE/ISC) - 75% and above in English. Accepted State Boards - 80% and above in English. |
WAEC | C6 or above |
Do you need to complete a Pre-Sessional English course to meet the English language requirements for this course?
The length of Pre-Sessional English course you’ll need to take depends on your current level of English language ability.
Find out the length of Pre-Sessional English course you may require for this degree.
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Last updated 11 November 2024 / / Programme terms and conditions