Applied Bioinformatics and Genomics (MSc)

How will I be taught?

The programme is delivered as face-2-face learning. You will find course materials, links to related materials and assessments via Cardiff University’s Virtual Learning Environment (VLE) ‘Learning Central™’.

Delivery approach:

• Each taught Module will be delivered using a small-group classroom-model (< 20 participants per session).
• You will be expected to commit to approximately 200 hours of effort per module; from this you will receive approximately 60 hours of face to face contact. This will be delivered through approximately 20 teaching sessions. Each teaching session will be 3-hours with appropriate breaks.
• Teaching sessions will include a combination of elements such as theory (blackboard learning), computer practical, group-work and tutorial. We believe that to achieve learning outcomes for a bioinformatics-based course it is not often useful to deliver extensive ‘lecture-only’ sessions. We believe you will learn through application and interaction. However, where appropriate, some theory will be delivered as lectures.
• Each session will take a variety of forms, but the overall structure will be to achieve 2-3 key learning outcomes per session via introduction to key concepts, conveying relevant up-to-date information and exposure to research methodology and application.
• In the teaching sessions, we will provide feedback on formative assessments and course content. In these elements, you will have the opportunity to discuss themes or topics, to consolidate and get feedback on your individual learning and to develop skills in oral presentation. Communication skills will be developed in tutorials, where you will make individual contributions to group study; for example, by summarising a formative assessment or outcomes from group sessions.
• You will practise and develop theory, intellectual skills, team-work and presentational skills by participating in diverse learning activities, such as solving bioinformatics problems, small-group discussions, oral presentations, independent research tasks and written assignments. 
• You may be taught alongside students from other Programmes, including the MSc in Bioinformatics and Genetic Epidemiology as well as students undertaking Continuing Professional Development (CPD).

How will I be assessed?

Formative Feedback

Formative feedback is feedback that does not contribute to progression or degree classification decisions.  The goal of formative feedback is to improve your understanding and learning before you complete your summative assessment. More specifically, formative feedback helps you to:

• identify your strengths and weaknesses and target areas that need work;
• help staff to support you and address the problems identified – allowing targeted strategies to be developed for your improvement.
• The development of skills in data sciences requires practice. You learn through your successes and failures. You will receive short questions and tasks as part of the teaching sessions. These formative tasks will help reinforce your learning and provide useful feedback to the course co-ordinators about where we can improve and focus resources. Although formative marks will not contribute to progression or degree classification decisions, appropriate investment in these tasks will assist the summative elements of the Module.

Summative Feedback

• Summative feedback is feedback that contributes to progression or degree classification decisions.  The goal of summative assessment is to indicate how well you have succeeded in meeting the intended learning outcomes of a Module and will enable you to identify any action required to improve.  To maintain consistency and standards, markers of assessments make use of pre-defined marking scheme for each assignment. All feedback should directly link to the Module grading / assessment criteria.

• Our preferred feedback methods include coursework and presentation. Students will generally receive two coursework elements; a theory-driven review paper (e.g. a “compare and contrast” essay), and an applied research project. Students will be required to present their findings of their research to their peers and examiners as part of the summative assessment process.

• Formative feedback will be communicated to the students through electronic and written means in a timely manner. Additional feedback, to the group, will be provided as part of the tutorial components of the teaching sessions. Summative feedback on assessment will be delivered within the timeframe set by the University.

Overall Assessment Strategy

The implemented assessment strategy will evaluate;

• Knowledge and Understanding: Coursework will include data analysis, reviews and programming exercises and will be assessed through written reports.
• Intellectual skills: Assessment of intellectual skills will be via problem-based exercises/assignments, and case study reports. Evaluation of your understanding of the material will also be assessed through presentation. Where applicable these skills will be assessed via the dissertation, interview research project and critical review.
• Practical skills: Practical skills will generally be assessed via practical based assignments. Where applicable these skills will need to be demonstrated within the dissertation, research project and critical review. Assessment of such practical skills will be incorporated into the final grading for the dissertation.
• Transferable/key skills: Assessment of written communication skills will be via report writing and the dissertation (where applicable). Oral presentations comprise part of the assessment on selected modules and team working skills will be assessed during the collaborative assignment.
• MSc Dissertation: The dissertation stage will be assessed based on the final dissertation. The dissertation shall be assigned 60 credits and, in combination with the taught stage(s), shall be weighted 50% for calculating your final mark. Expectations for the format, submission and marking of the dissertation will follow current Senate Assessment Regulations, supplemented where appropriate with additional requirements of the Programme/School/College and any specific requirements arising from the nature of the project undertaken. We will provide guidelines to the students to how assessments will be made for their dissertations. 

We are committed to equality for the English and Welsh languages and if you are a Welsh speaker you may request to have a Welsh-speaking Personal Tutor, and undertake your assessments through the medium of Welsh. 

How will I be supported?

As part of the induction process, we host a 2-hour welcome session for all students – so that you can meet your fellow students, the course management and the teaching team. We also provide an induction session related to tutoring and library services and resources. All students will be provided with an up-to-date student handbook, provided in the appropriate college format.

A personal tutoring system exists to guide you through the course with the aim of encouraging both academic success and personal well-being and development. At the start of the course you will meet with your Personal Tutor to ascertain and discuss your perceived areas of strength and weakness (using the pre-course questionnaire answers as a starting point for discussion). This will cover subject areas of study, English language capability and track record in past examinations.

Specific learning differences, disability and/or medical conditions will be identified and the Programme Director will follow university procedures and guidance on this. We are committed to equality for the English and Welsh languages and if you are a Welsh speaker you may request to have a Welsh-speaking Personal Tutor.

From an academic viewpoint, your tutor is there to provide guidance on any general academic issues/questions arising from the course and to encourage you to pursue self-directed learning. The role of the tutor is not to read or mark assignment drafts, but they can communicate with you about any topic that you may find challenging. Detailed feedback from the Module Team is given to students once an assignment has been marked. You are welcome to discuss this feedback with your tutor

During the MSc dissertation stage, each student will be allocated a Dissertation Supervisor who will guide their planning and advise them as they complete their projects.

What skills will I practise and develop?

Upon completing the Programme, you will be able to demonstrate:

• a systematic understanding of the principles of statistics, biosciences and computer science that are the foundations of genetic epidemiology and bioinformatic;
• a knowledge of current bioinformatics software and databases and their applicability to solving bioinformatics problems in the field and in their own research;
• a keen awareness, understanding and critical appreciation of the wide variety of statistical methods available to analyse genetic data together with appreciation of the issues involved in study design;
• a knowledge of statistical software used to analyse omics data and the situations in which the packages should/should not be applied;
• integrate acquired knowledge and understanding with practical skills resulting in a sound approach to problem solving;
• synthesise information from a variety of sources at the forefront of Genomics and Bioinformatics;
• critically evaluate different approaches to solving problems and to demonstrate their applicability, strengths and weaknesses;
• formulate hypotheses and use analytical skills to test these hypotheses. Interpret the results and make decisions in the light of all available information in possibly complex and unpredictable situations;
• undertake a semi-independent piece of original research or critical review demonstrating self-initiative, responsibility for planning and carrying out tasks, tackling and solving research problems;
• the ability to assess the correct type of analysis for a dataset and to perform it using an appropriate computer package;
• competency in accessing and using bioinformatics tools from a variety of sources;
• computer programming skills and competency in good program design;
• the ability to design, implement and analyse algorithms for bioinformatics applications;
• the ability to produce case study reports on major topics within the fields of bioinformatics and biostatistics;
• competent research skills such as literature searches;
• work independently, to manage his/her own time and to take responsibility for learning required for continued professional development;
• effectively manage individual tasks and larger scale projects identifying and resolving possible obstacles;
• work as part of interdisciplinary teams, identifying individual’s strengths and weaknesses and allocating work accordingly to meet the team’s objectives;
• competently use information technology such as e-mail, word-processors, software tools and the world-wide web;
• transfer computing skills and concepts to subsequently unfamiliar packages/languages/databases;
• present information, understanding and arguments using effective communication (written and oral) with awareness of intended audience.