Bioinformatics MSc/Diploma/Certificate

Designed to prepare you to interact with the world’s most advanced biological and clinical datasets - this programme will prepare you for careers, or further graduate work, in the omics-enabled biosciences. 

The future of biology is bioinformatics – computational analysis procedures that leverage state-of-the-art statistics and machine learning to gain insight into systems of exquisite complexity. We have entered an era of unprecedented expansion in the biological sciences, and our data now grows exponentially faster than Moore’s law. 

The biological sciences have been transformed by the advent of omics. Enabled by revolutionary advances in molecular sequencing and mass spectrometry, it is now possible to sequence a genome in six hours, simultaneously assess the expression level of every gene in a genome, quantify the abundance of proteins and metabolites, and determine the epigenetic and regulatory landscape of individual cells. Hypotheses are generated through the integrative analysis of enormous datasets, and tested in high-throughput with third-generation genome-engineering technologies, including CRISPR. 

Biology is now driven by data. 

Scholarships available 

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We are offering scholarships of £2000 to outstanding students. No separate application is required - you just need to be in receipt of an offer by  31 May 2017. 

  Find out more about our Global Scholarships for Excellence   

This course is composed of five taught modules, one group project, and one independent project. The taught modules provide you with foundational knowledge and skills in statistics, computer programming, and molecular biology, and then exploit this skillset to help you to understand and participate in the ongoing revolution in biological data science.

The course begins with a fast-paced introduction to essential capabilities. Through individualized and student-centered teaching, as well as heterogeneous group work, it will prepare wet-bench biologists and clinicians interested in data analysis, as well as statisticians or computer scientists wishing to work in biology for studies in modern bioinformatics.

You will then be introduced to the sequencing modalities that have reduced the cost of obtaining the human genome from over a billion pounds to less than a thousand dollars, and the many applications in the biomedical and environmental sciences enabled by these technologies. Beyond DNA and RNA sequencing, you will learn how mass spectrometry and nuclear magnetic resonance spectroscopy have opened protein sequencing and metabolomics – the study of all small molecules, or metabolites present in a system. You will learn how to integrate these datatypes with high-content imaging to map molecular changes onto four-dimensional representations of complex systems, including the human nervous system and fresh-water ecologies.

Closely supervised individual projects will prepare you to tackle real-world research or industrial problems at scale, and highly interactive group projects will enable teams to tackle challenges too complex for individuals. Projects are developed in collaborations with our world-leading faculty and our many industrial partners in the West Midlands, ensuring that you are equally prepared for academic or industrial career paths. 

Why study this course

  • Learn how to analyse each major omics data-type – beyond next generation sequencing, understand mass spectrometry, emerging single molecule techniques, genome engineering, and integrative analysis toolsets that reveal synergies between these and other distinct modalities such as Health Partners
  • Gain a foundation in statistical machine learning to prepare for a career in the information sciences
  • Explore the frontiers of biosciences, from precision medicine, to precision agriculture, and emerging fields including molecular ecosystems biology and topological data analysis.  
  • Expand our foundational understanding of human genome biology working with experts in the West Midlands Genomic Medicine Centre: University Hospital Birmingham is a major contributor to the 100,000 Genomes Project, which is closely integrated with this MSc in Bioinformatics
  • Discover new opportunities in one of the fastest growing industrial and academic fields in the United Kingdom and beyond. 

Modules

The modules on the programme are as follows (please find more details below):

  • Essentials of Biology, Mathematics and Statistics (20 credits)
  • Genomics & Next Generation Sequencing (20 credits)
  • Data Analytics & Statistical Machine Learning (20 credits)
  • Metabolomics and advanced (omics) technologies (20 credits)
  • Computational Biology for Complex Systems (20 credits)
  • Interdisciplinary Bioinformatics Group Project (20 credits)
  • Individual Project (60 credits)

Essentials of Biology, Mathematics and Statistics (20 credits)

This module will provide an introduction (or refresher) to essential biological and quantitative theory that underpins modern bioinformatics. Concepts will be introduced via a series of core problems whose details will be explored in greater depth in later modules. 

Quantitative topics will include:

  • Linear Algebra: basic matrix-vector operations, least-squares
  • Probability Theory: Rules of Probability, Conditional Probability, Bayes’ Rule, distributions
  • Descriptive Statistics: summary statistics, visualisation
  • Hypothesis Testing: Fisher exact, chi-square, t-test
  • Correlation and Causation: Parametric and non-parametric measures
  • Introduction to Statistical Modelling in the R programming language: linear models, estimation

Furthermore, this module will go through the very essential of biology, biochemistry and biotechnology including cells, proteins, DNA and genes in to reach a level where you are on par to understand the mandatory modules.

The module contains a variety of integrated learning environments, including interactive lectures as well as tutorials to explain and give feedback on aspects of assessment.

By the end of the module you will be able to:

  • Understand essential mathematical and statistical concepts and apply the correct techniques to solve elementary data analysis problems
  • Correctly apply techniques for the graphical representation and visualisation of data
  • Perform essential statistical data analysis in a computer programming language, specifically R
  • Understand essential concepts in cell biology and genetics such as the role of DNA, RNA and Proteins and their relation to specific bioinformatics problems.
  • Solve quantitative problems inspired by real world bioinformatics that require an understanding of the underlying biology and the application of the correct mathematical and statistical techniques
  • Demonstrate the qualities and transferable skills necessary for employment requiring the exercise of initiative and personal responsibility, decision making in complex and unpredictable situations, and the independent learning ability required for continuing professional development

Genomics & Next Generation Sequencing (20 credits)

This module will introduce the you to various sides of *Omics:

  • Genomics
  • Transcriptomics
  • Methylation
  • Transcription factors analysis
  • RNA binding protein analysis
  • Chromatin accessibility analysis (e.g. DNase-seq, ATAC-seq)
  • Chromatin structure analysis (e.g. HiC, ChIA-PET)

The module will include a coverage of the technological progress:

  • History: Sanger sequencing through array technologies
  • Next generation Sequencing
  • Advanced library construction procedures for specialized assays, including ChIP, DNase, ATAC, HiC, eCLIP, and others

This module will also address specific fields of Classical Genetics, Population Genetics and Cancer Genomics. It will involve a biological, technological and analytical dimension to help you design the best experiment with the appropriate data type and enable its analysis with the latest state of the art approaches.

By the end of the module you should be able to:

  • Understand the biological interpretation of the various *omics fields, especially DNA, RNA and Methylation based.
  • Understand the various technologies available to measure the various type of information from Sanger sequencing, micro-array, Mass-Spectrometry to Next Generation sequencing
  • Analyse the various types of data generated in the field both with command line and web interface such as Galaxy
  • Integrate the various type of data to understand the biological implication of the results
  • Deal with the complexity of information available to enable the integration of diverse data types

Data Analytics & Statistical Machine Learning (20 credits)

The aim of the module is to provide an in-depth understanding of the state of the art in data integration, mining and analysis with applications in biology and biomedicine.

The module covers topics related to data:

  • Data types,
  • Data modelling,
  • Data management,
  • Semantic representation,
  • Integration,
  • Analysis

The module will include various statistical techniques:

  • Frequentist and Bayesian approaches,
  • Univariate and multivariate analysis,
  • Specific statistics definition.

Furthermore it will present Modelling and Optimisation approaches to deal with large structured, yet heterogeneous, dataset and will include several techniques

  • Hidden Markov Models,
  • Self Organizing Maps,
  • Boot-strapping and resampling procedures,
  • Agent-based modelling,
  • Statistical Machine Learning.

The module will aslo provide methods to analyze, visualize and integrate the various types of data and includes training on several well used web-based resources such as OMIM, TCGA, DAVID, REACTOME

By the end of the module you will be able to:

  • Demonstrate a good understanding of complexity of omics and clinical data and their management including their semantic representation
  • Demonstrate an in-depth understanding and ability to perform Data integration, mining and analysis
  • Demonstrate conceptual understanding of Computing, Algorithmic and Programming that enables the student to evaluate methodologies and develop critiques of them and, where appropriate, propose new methods
  • Deal with the complexity of information available to enable the integration of diverse data types
  • Demonstrate self direction and originality in tackling and solving problems to perform the appropriate Modelling and Optimization

Metabolomics and advanced (omics) technologies (20 credits)

This module will introduce you to metabolomics, and you will learn about the data processing and data analysis approaches (e.g. biostatistics and metabolite identification) that are used to interpret data and extract biological insight from the large metabolomics data sets. You will also be introduced to the analytical approaches (e.g. mass spectrometry and NMR spectroscopy) that are used in metabolomics, so that you can appreciate the challenges involved in producing robust and reproducible data sets.

Additionally, this module will introduce you to other emerging and advanced (omics) techniques, including bioimaging and spectroscopy.

The course will include a combination of interactive seminars, hands-on computer workshops, tutorials and a tour of the new Phenome Centre Birmingham.

By the end of the module you will be able to:

  • Demonstrate a conceptual understanding of metabolomics, biological imaging and other advanced bioscience technologies.
  • Demonstrate a conceptual understanding of the major challenges facing metabolomics, biological imaging and other advanced bioscience technologies.
  • Demonstrate a conceptual understanding of a typical bioinformatics workflow to process and analyse metabolomics datasets.
  • Perform basic bioinformatics data analysis and extract biological insight from large metabolomics data sets.

Computational Biology for Complex Systems (20 credits)

This module focuses on big data-driven science leveraging diverse omics modalities in the environmental, ecological and toxicological areas. This module will draw from the fields of molecular biology, genomics, genetics, evolutionary biology, computational biology, toxicology, and risk assessment –though these are not prerequisites for enrolment. Theory and concepts will be highlighted by real world applications drawn from the scientific literature. By involving instructions from industry, government agency and NGO scientists, it means to offer you a variety of dynamically evolving career paths.

Specifically it will contain 3 parts:

  • Introduction to Environmental, Ecological and Toxicological Sciences and practical examples – with a focus on research conducted in the University of Birmingham Macrocosms. In the first year, this will focus specifically on BIFoR and DRI-STREAM.
  • Data types and problems faced in the study of highly complex environmental and biological systems.
  • Computational approaches specific to the field such as complexity theory, hierarchical models, ecological models, population dynamics, and the emerging fields in which Birmingham faculty play a world-leading role: phylogenomic toxicology and molecular ecosystems biology.

By the end of the module you will be able to:

  • Demonstrate a fundamental technical understanding of Omics technologies (transcriptomics and metabolomics), high-throughput in vivo and in vitro assays, computational approaches as applied to environmental, ecological, and holobiotic systems (animals and/or plants + their microbiomes)
  • Demonstrate a systematic understanding of the emerging field of Molecular Ecosystems Biology, including an emphasis on biotic-abiotic interactions, and the role of the microbiome in establishing the health and resiliency of organisms. 
  • Demonstrate a  conceptual and mechanistic understanding of integrative analysis techniques for multi-omics data – and the ability to apply these techniques to their own research
  • Demonstrate a  systematic understanding and critical awareness of the implications of research in Biology related fields, especially ethically

Interdisciplinary Bioinformatics Group Project (20 credits)

This module will pull together students from various backgrounds to tackle an inter-disciplinary project, using mathematical and/or computational approaches to address a real-world research question involving biological data.

You will have lectures on how to prepare scientific publications, posters and presentations as well as on the ethics requirements of research.

You will work in group of 3-5 on a real-life problem proposed by an academic member of UoB or external collaborators. You will have to find the relevant literature, and apply the relevant analytical methods to generate new information that will be presented as a group and individually.

By the end of the module you will be able to:

  • Work effectively in an interdisciplinary team
  • Carry out a relevant literature search for their topic
  • Demonstrate a comprehensive understanding of the broad world of *Omics in the context of complex biological, clinical, or environmental data.
  • Choose appropriate computational and/or mathematical approaches to perform analysis of *Omics data; evaluate methodologies and develop critiques of them and, where appropriate, propose new methods
  • Demonstrate a systematic understanding and critical awareness of the implications of research in biology-related fields, including an understanding of ethics
  • Present the results of the project in written and oral form.

Individual Project (60 credits)

This module will put you in real-life situation of a bioinformatics project with practical problem to solve proposed by an academic member of UoB. You will have to find the relevant literature, and apply the relevant analytical methods to generate new information and present in written and oral form.

By the end of the module you will be able to:

  • Present your topic background, approach, analysis, results and conclusionsin in written and oral form 
  • Perform a bioinformatics analysis and/or development for the project
  • A conceptual understanding of Computing, Algorithmic and Programming that enables the student to evaluate methodologies and develop critiques of them and, where appropriate, propose new methods
  • Demonstrate self direction and originality in tackling and solving problems to perform the appropriate Modelling and Optimization
The qualities and transferable skills necessary for employment requiring the exercise of initiative and personal responsibility, decision making in complex and unpredictable situations, and the independent learning ability required for continuing professional development

Related staff

Fees and funding

Fees

2017/18 

Home/EU
MSc - £7,020
PGDip - £4,680
PGCert - £2340

Overseas
MSc £19,890  

Self funding students can choose to pay in instalments by direct debit.

Learn more about fees and funding.

Postgraduate Loans for Masters students

You can apply for a government loan of up to £10,000 per student for postgraduate Masters study. This is a contribution towards the costs of study and whether the loan is used towards fees, maintenance or other costs will be at the discretion of the student. Find out more about the Postgraduate Loan.

Scholarships

Overseas Research Scholarships

International students can often gain funding through overseas research scholarships, Commonwealth scholarships or their home government. Visit our website for information about scholarships for international students.

For information about all Home/EU and International funding opportunities please visit the Postgraduate Funding Database.

For other funding queries contact the School directly or get in touch with the Student Funding Office via the online enquiries system.

Entry requirements

2:1 or equivalent in Biology, Mathematics, Computer Science or other relevant subjects

International students:

English language requirement
You can satisfy our English language requirements in two ways: 

English to IELTS 6.5 (with no less than 6.0 in any band). 

If you need help with your English language skills then support is available. 

The English for Academic Purposes Presessional course is for international students who have a conditional offer to study at the University, but who do not currently meet the English language requirements. The course is tailored to your level of English and allows you to meet the English language requirements for your programme without retaking IELTS. The EAP programme runs throughout the year and offers different programme lengths ranging from 42 weeks to 6 weeks. The length of course you need depends on your future course, your existing IELTS score and the English level you need for your university degree.

Find out more about the English for Academic Purposes Presessional course.

How to apply

When clicking on the Apply Now button you will be directed to an application specifically designed for the programme you wish to apply for where you will create an account with the University application system and submit your application and supporting documents online. Further information regarding how to apply online can be found on the How to apply pages

Apply now

As a Birmingham student, you will be joining the academic elite and will have the privilege of learning from world-leading experts, as well as your peers. From the outset you will be encouraged to become an independent and self-motivated learner. We want you to be challenged and will encourage you to think for yourself.

Teaching will take place in a combination of taught lectures, seminar, practicals as well as group and individual projects. Most lectures and practical will take place within the lecture room at the heart of the Centre for Computational Biology which is equipped with advanced multimedia facility to enable recording and remote interaction.

You will have access to a comprehensive support system that will assist and encourage you, including personal tutors who can help with both academic and welfare issues.

Bioinformatics is one of the fastest growing fields in industry and academia and at any given time and the need for competent bioinformaticians far outstrips availability. 

The numbers of industry and academic job openings in and around the West Midlands are growing rapidly. The following articles show the recent surge in popularity of this subject:

Nature - Spotlight on Bioinformatics

Science - An Explosion of Bioinformatics Careers

Careers Support for Postgraduate Students

Careers Network – We can help you get ahead in the job market and develop your career

We recognise that as a postgraduate student you are likely to have specific requirements when it comes to planning for your next career step. Employers expect postgraduates to have a range of skills that exceed their subject knowledge. Careers Network offers a range of events and support services that are designed for all students, including postgraduates looking to find their niche in the job market. The Careers Network also have subject specific careers consultants and advisers for each College so you can be assured the information you receive will be relevant to your subject area. For more information visit the Careers Network website

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