Master of Science in Bioinformatics of Infectious Diseases and Pathogen Genomics

Purpose

The Master of Science in Bioinformatics of Infectious Diseases and Pathogen Genomics is composed of core modules on Bioinformatics and a research thesis. Learners must select one of the two capita selecta modules: Infectious Diseases or Pathogen Genomics. All learners engage in the bioinformatics analysis of data generated in either the Infectious Diseases or the Pathogen Genomics fields and present the results of their research as a seminar and in the form of a thesis.

Learners will be engaged with knowledge and research focusing on the formulation of a bioinformatics approach within the full framework of the biological field typically results in a more reliable and deeper generation of new knowledge. The knowledge and research acquired will make a substantial and immediate contribution to the analysis and mining of datasets in Infectious Diseases and Pathogen Genomics and are expected to have a direct impact on human health and thus, society.

The learners will be supported in acquiring extensive knowledge and research skills in Bioinformatics of Infectious Disease and Pathogen Genomics. Not only will they meet an urgent need in society to produce scientists who can follow a bioinformatics approach in biology, but they will also develop crucial skills in informatics that match the demands of innovative research in these fields. In doing so they will become critical and creative thinkers who can take responsibility for their learning and how they use knowledge.

The further research and study focus for learners would then focus either on engagement with Bioinformatics data in Infectious Diseases and Pathogen Genomics in the context of research groupings, or progression to a PhD in Bioinformatics, and eventual assumption of Principal Investigator or Team Leader roles in academia or industry.

After completion of the qualification, the qualifying learner will be able to

• Critically analyse bioinformatics research literature in the field of infectious diseases and pathogen genomics.
• Identify the most appropriate, current bioinformatics methods and tools required to solve a problem in infectious diseases or pathogen genomics.
• Apply skills in statistics and computer programming in the bioinformatics field.
• Review the scientific literature in the field of bioinformatics of infectious diseases and pathogen genomics and present it with appropriate communication skills to a scientific audience.
• Plan and execute supervised research in the field of Bioinformatics of Infectious Disease or Pathogen Genomics.

In developing the knowledge and skills to attain the exit level outcomes, learners will be guided and supported to manage continued learning and keep abreast of field-specific as well as general scientific advances and take responsibility for his/her development, to be effective in a diverse environment and to be able to solve problems.

Rationale

The proposed structured master's qualification will, apart from extensive training in general Bioinformatics, also have capita selecta modules in Infectious Diseases and Pathogen Genomics. In these modules, unique topics and bioinformatics approaches will be covered to supplement the general bioinformatics training of the core module. These modules will also cover the specialized biology in Infectious Diseases or Pathogen Genomics to a suitable biological depth to enable appreciation and engagement with data in the full biological context of the question. Experience has shown that formulation of a bioinformatics approach within the full framework of the biological field typically results in a more reliable and deeper generation of new knowledge.

This qualification was widely discussed among various stakeholders in the faculties of Medicine and Health Sciences, Science and AgriSciences, as well as with national and international collaborators and partners.

The further research and study focus for learners would then focus either on engagement with Bioinformatics data in Infectious Diseases and Pathogen Genomics in the context of research groupings, or progression to a PhD in Bioinformatics, and eventual assumption of Principal Investigator or Team Leader roles in academia or industry.

Additionally, this qualification will produce bioinformaticians who are well-versed in the biology and specialised bioinformatics methods and approaches associated with Infectious Diseases and Pathogen Genomics, including diagnosis, disease progression, treatment, and outcome assessment. This will make a substantial and immediate contribution to the analysis and mining of datasets in Infectious Diseases and Pathogen Genomics and is expected to have a direct impact on human health and thus, society.

Recognition of Prior Learning (RPL)

The Faculty of Science and the Faculty of Medicine and Health Sciences endorse the Regulation for the Recognition of Prior Learning (RPL) and Credit Accumulation and Transfer (CAT) approved by the Council of Stellenbosch University and has delegated the supervisory function regarding the assessment of RPL to its departments because the subject-specific academic expertise resorts within the academic departments. Respective academic departments where applications are served are responsible for the implementation of the RPL policy, as well as recommendations regarding credited recognition of proven prior learning. A recommendation is made by the departments, in consultation with the relevant Program Coordinator to the Academic Committee of the Faculty Board.

Learners can thus specifically apply to be accepted to the structured MSc (Bioinformatics of Infectious Diseases and Pathogen Genomics) by the RPL or CAT route.

The Postgraduate Committee of the Centre for Bioinformatics and Computational Biology will consider all such applications and weight of the formal (CAT) and non-formal or informal learning (RPL) against the knowledge required to successfully complete the requirements of the MSc degree.

Extensive professional experience in a broad variety of modern bioinformatics analyses, for instance, may qualify the student not to be required to complete the full bioinformatics module in the structured MSc degree programme. A recommendation will then be made to the Academic Committee of the Faculty Board. This selection will be performed in accordance with the CAT and RPL rules accepted by the Council of Stellenbosch University, and according to the rules of the faculties of Science, AgriScriences, or Medicine and Health Sciences.

As an example, a learner with a BScHons degree in Computer Science and who has participated in the development of tools to analyse biological data will be interviewed to assess whether the level of knowledge is suitable to pursue this MSc programme.

Entry Requirements

The minimum entry requirement for this qualification is

• Bachelor's degree in the cognate field, NFQ level 8

Or

• Bachelor of Science Honours degree, NQF level 8

Or

• Bachelor of Science Honours in Bioinformatics and Computational Biology, NQF Level 8.

This qualification consists of the following compulsory and elective modules at National Qualifications Level 9.

Compulsory Modules, Level 9, 155 Credits

• Bioinformatics, 35 Credits.
• Algorithms and Machine Learning for Bioinformatics, 10 Credits
• R-language for Bioinformatics,10 Credits
• Algorithms and Machine Learning for Bioinformatics, 10 Credits.
• Thesis, 90 Credits.

Elective Modules, Level 9, 25 Credits (Select one)

• Infectious Diseases, 25 Credits.
• Pathogen Genomics, 25 Credits.

Exit Level Outcomes

1. Critically analyse bioinformatics research literature in the field of infectious diseases and pathogen genomics.
2. Identify the most appropriate, current bioinformatics methods and tools required to solve a problem in infectious diseases or pathogen genomics.
3. Apply skills in statistics and computer programming in the bioinformatics field
4. Review the scientific literature in the field of bioinformatics of infectious diseases and pathogen genomics and present it with appropriate communication skills to a scientific audience.
5. Plan and execute supervised research in the field of Bioinformatics of Infectious Disease or Pathogen Genomics.

Associated Assessment Criteria

Associated Assessment Criteria for all Exit Level Outcome

The following Associated Assessment Criteria are assessed in an integrated manner across all the Exit Level Outcomes

• Present a short talk on and display an understanding of current topics in Machine Learning.
• Critically evaluate and present a current topic in Machine Learning, demonstrating its potential application for accurate data analysis in bioinformatics through a chosen research topic or case study.
• Design appropriate and creative methods to apply to complex problems in bioinformatics
• Design and implement comprehensive bioinformatics pipelines, effectively utilising them to solve complex problems in infectious diseases and pathogen genomics.
• Formulate solutions to epidemiological challenges in infectious diseases and genomics.
• Develop bioinformatics analysis pipelines for infectious diseases and genomics data.
• Design algorithms and effective code to perform computational tasks.
• Produce error-free, correctly executing Python code to address complex problems in Bioinformatics.
• Leverage appropriate data sets and write optimised Python code to effectively solve complex bioinformatics problems. (This condenses the focus on technical skills and results-oriented coding).
• Use suitable data sets to develop scripts that solve complex problems in bioinformatics.
• Develop a comprehensive research proposal with clear research questions and aims for a chosen topic in bioinformatics of infectious diseases or pathogen genomics.
• Design a robust research methodology with appropriate ethical considerations, inquiry process, hypotheses, and theoretical frameworks for analysing findings in the chosen research topic.
• Effectively communicate research findings through clear and logical presentations and written reports, applying relevant theories and concepts to answer the research question and draw conclusions.
• Structure the thesis effectively, clearly defining the research field and subject, and presenting the research, results, discussion, scientific contributions, conclusions, and future directions in a logical and cohesive manner.
• Illustrate thorough familiarity with relevant literature and effectively integrate it into the thesis, utilizing proper referencing and academic writing practices.
• Support all written arguments with relevant literature, using the correct referencing system and applying sound academic writing practices to avoid plagiarism.
• Utilise appropriate academic writing and referencing to formulate a clear, well-written thesis.
• Deliver a thesis that includes an introduction chapter, followed by several chapters outlining the research, followed by a discussion chapter of the research results of the whole dissertation, highlighting the scientific contributions of the study, followed by a conclusion and future directions.