2024/25 Taught Postgraduate Module Catalogue
MEDM5161M Methods in Biomedical Research
15 creditsClass Size: 70
Module manager: Dr Georgia Mavria
Email: g.mavria@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2024/25
Pre-requisite qualifications
As per parent programme specificationModule replaces
NoneThis module is not approved as an Elective
Module summary
In this module, students will gain an understanding of the principles of scientific research as applied in Biomedical Sciences. They will be taught the process of formulating an original question within a research field of interest, the principles of good project design, and ethical considerations that arise in biomedical research. The module will provide insight into different research approaches commonly applied in biomedical research, ranging from laboratory imaging, immunological and organotypic systems approaches to clinical trials. Using examples of real research, students will gain understanding of the process of experimentation and data collection, with hands on experience analysing and interpreting laboratory and patient data. Students will evaluate data and consider potential sources of bias and error. The module will conclude with the process of integration of different lines of experimentation, and writing of a scientific report.Objectives
The major objectives of this module are to develop skills and knowledge in:1. The principles of project planning and experimental design in Biomedical research
2. Ethical issues that arise and the process of obtaining Ethics approval for animal and patient research
3. Different lines of experimentation and the types of data they generate
4. Data analysis and application of appropriate statistical methods
5. Data evaluation and integration
6. Report generation and the process of journal submission and peer review
Learning outcomes
1. Identify subject of study within a niche area, critically appraise published data & develop original/ null hypotheses.
2. Apply general principles of project design to evaluate hypotheses - define objectives, experimental design, milestones & contingencies.
3. Explain and summarise ethics in animal work, patient ethics, human tissue / cell lines (HTA), issues of consent & principles of professional conduct.
4. Apply different research approaches and exhibit mastery over the types of data they generate including hands on analysis of imaging data, immunological data, in vivo data, clinical and other big data.
5. Critically assess the general principles of robust experimental planning, requirement of independent experiments, technical versus biological repeats, use of multiple models as appropriate for a research approach.
6. Demonstrate comprehensive understanding of what statistical methods are appropriate for type of data- calculate using appropriate software statistical estimates of precision and hypothesis tests of significance.
7. Critically interpret and evaluate data arising from different approaches, identify potential sources of error and bias, integrate different lines of experimentation.
8. Understand the process of report/ paper submission, peer review and publication.
Syllabus
This module will draw on the expertise of world class biomedical research staff at the Faculty of Medicine and Health both clinical and non-clinical.
The module will begin with examining how a research question and original hypothesis can be generated through mining available literature within a particular field. Different types of research questions will be discussed. Those that aim to shed light to existing understanding, for example through obtaining mechanistic insights, and others that aim to uncover new physiological or pathological processes, and/or deal with therapeutic interventions.
The next stage will focus on the fundamental principles of planning of a research project, including setting out a general strategy, defining specific objectives, deliverables with timelines, milestones and contingencies. Ethical issues that arise will be discussed alongside basic principles of academic integrity and professional conduct.
A lecture and practical will introduce students to general principles of application of statistical methods in biomedical research, and use of appropriate software for statistical analyses (Prism GraphPad). Using these tools students will analyse real data obtained from our research laboratories and clinics, and learn how to describe the data using text, tables, charts, and figures, and analyse using statistics tests, including simple parametric and non-parametric analyses through to more complex approaches such as regression.
The course will explore different research approaches and types of data that they generate. Those will include cell biology, virology and immunological approaches, in vivo work, organoid and organotypic systems, and clinical cancer research. A series of lectures complemented by tutorials running in parallel will cover the handling of data arising from commonly used imaging software such as Columbus, Volocity and Qpath; handling analysis, and interpretation of virology and immunological data, for example arising from FACS analyses; in vivo data from in-house experiments. Lecture and tutorial will focus on the principles of clinical trial design, analysis and interpretation of clinical data for example arising from variable duration of follow-up in cohort studies.
The course will conclude with discussions on interpretation and evaluation of data arising from different research approaches, identification of potential sources of error and bias, drawing of conclusions based on different lines of experimentation, and compilation of a scientific report. The process of submission to scientific journals for publication, and peer review will be explored.
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 15 | 1.00 | 15.00 |
| Practical | 1 | 1.00 | 1.00 |
| Tutorial | 1 | 0.50 | 0.50 |
| Tutorial | 6 | 2.00 | 12.00 |
| Private study hours | 121.50 | ||
| Total Contact hours | 28.50 | ||
| Total hours (100hr per 10 credits) | 150.00 | ||
Private study
Students will be expected to carry out private study related to each lecture, tutorial and practical as necessary using reading lists that will be provided. Data for analysis will be given to the students one week prior to the tutorial together with instructions and access to statistics software. Compilation of the project report will require searches of the relevant literature.Opportunities for Formative Feedback
Students will be encouraged to question and participate during the lectures and tutorials, allowing informal monitoring of their level and progress.The students will receive informal feedback in relation to how they apply appropriate analytical and statistical methods for data analysis during the course of tutorials and practical sessions. This will allow for informal monitoring on progress.
The module leader will also occasionally contact the tutors and the student to receive independent feedback of the student progress.
Students will also document their experience with a reflective log which will be used to monitor that they develop the appropriate skills set out in the skills objectives.
Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Report | Project report | 60.00 |
| In-course MCQ | 1 hour | 40.00 |
| Reflective log | 200 words - Formative | 0.00 |
| Total percentage (Assessment Coursework) | 100.00 | |
Compensation applies
Reading list
The reading list is available from the Library websiteLast updated: 29/04/2024 16:18:11
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