MSc
Duration: 1 year full-time
Overview
Please note: the name of this course has changed from MSc Functional Omics to Msc Applied Genomics. You may see this course referred to as MSc Functional Omics in print and other materials.
This Master’s course will teach you how to generate and handle “big data (omics)” associated with biological processes and diseases. You will learn to extract the relevant information and perform functional analysis and validation of your selected targets You apply novel experimental techniques in the laboratory to leverage large amounts of data towards understanding the causes, and potentially find cures, for diseases.
This course will be especially appealing to students with a background in biology, genetics, biochemistry, medicine and related areas and for those who are interested in a career in modern biomedicine, whether going on to study a PhD in academia or straight to work in biomedical industry.
The course will prepare you to perform quantitative data analysis at scale, and design and perform experiments to enable you to interpret the results meaningfully. This will provide a key skill in modern biomedicine, in the pharmaceutical industry and beyond.
Study programme
During the first four months, you will acquire theoretical knowledge on how to mine biomedical data to find interesting genes associated with a particular disease as well as on the experimental tools (in vitro and in vivo) that you can use in the laboratory to test your hypotheses. In order to do so, you will attend lectures, workshops, journal clubs, demonstrations and practical laboratory sessions.
During the fifth month, you will select a biological or medical topic of your choice and prepare a report in the form of either a review or a PhD/grant proposal. This will equip you with a breadth of transferable skills essential to design a successful research programme, highly desirable in both academia and industry.
During the last six months of the MSc course, you will conduct a research project in one of our internationally recognized laboratories at Northampton. You will be able to choose from a wide range of projects, focused either on experimental research (“wet lab”) or with a strong computational component.
Structure
Modules shown are for the 2019-20 academic year and are subject to change depending on your year of entry.
Please note that the curriculum of this course is currently being reviewed as part of a College-wide process to introduce a standardised modular structure. As a result, the content and assessment structures of this course may change for your year of entry. We therefore recommend that you check this course page before finalising your application and after submitting it as we will aim to update this page as soon as any changes are ratified by the College.
Find out more about the limited circumstances in which we may need to make changes to or in relation to our courses, the type of changes we may make and how we will tell you about changes we have made.
Core modules
You take all of the core modules below.
Omics
An introduction to -omics (genomics, epigenomics, transcriptomics, proteomics, etc.) and the approaches to handle, understand and find targets from big data in biology.
Non-coding RNA, gene editing and in vitro modelling
Role of non-coding RNAs (miRNAs, CRISPR, etc.) and application of gene editing and other widely used laboratory research techniques in biology and medicine.
In vivo modelling and use of human material and data
Use of animal models and human samples to investigate mechanisms of disease.
Systematic review and grant/PhD proposal
A literature review on a topic of your choice leading to a scientific poster and a written review paper, PhD project or grant proposal.
Core and profesional skills
Training in basic laboratory skills during the performance of a mini researchproject (3 weeks long) designed by the students in groups.
Functional omics research project
Six-month laboratory project in a host research group leading to the production of an MSc thesis. Students will choose between wet laboratory-based and/or computational research projects.
Teaching and assessment
Teaching methods
- Laboratory project
- Laboratory sessions
- Online tests
- Seminars
- Small group teaching
- Systematic review
- Virtual Learning Environment (VLE)
Assessment methods
- Literature project thesis
- Laboratory project thesis
- Oral presentation of laboratory project and journal club
- Oral examination
- Poster presentation
- Team Based Learning
Entry requirements
We welcome students from all over the world and consider all applicants on an individual basis.
Minimum academic requirement
Our minimum requirement is a 2.1 degree in chemistry, biochemistry, physiology or a related biomedical science discipline.
Applicants who do not meet the academic requirements listed but who have substantial relevant industry experience may be admitted following completion of a Special Qualifying Exam.
International qualifications
We also accept a wide variety of international qualifications.
The academic requirement above is for applicants who hold or who are working towards a USA qualification.
For guidance see our Country Index though please note that the standards listed here are the minimum for entry to the College, and not specifically this Department.
If you have any questions about admissions and the standard required for the qualification you hold or are currently studying then please contact the relevant admissions team.
English language requirement (all applicants)
All candidates must demonstrate a minimum level of English language proficiency for admission to the College.
For admission to this course, you must achieve the standard College requirement in the appropriate English language qualification. For details of the minimum grades required to achieve this requirement, please see the English language requirements for postgraduate applicants.
How to apply
You can submit one application form per year of entry, and usually choose up to two courses.
Making an application
All applicants to our Master’s courses must apply online.