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PgCert Biostatistics and Bioinformatics

Academic Year 2021/22

A programme specification is required for any programme on which a student may be registered. All programmes of the University are subject to the University's Quality Assurance and Enhancement processes as set out in the DASA Policies and Procedures Manual.

Programme Title

PgCert Biostatistics and Bioinformatics

Final Award
(exit route if applicable for Postgraduate Taught Programmes)

Postgraduate Certificate

Programme Code

MED-PC-BB

UCAS Code

HECoS Code

100869

ATAS Clearance Required

No

Health Check Required

No

Portfolio Required

Interview Required

Mode of Study

Part Time

Type of Programme

Postgraduate

Length of Programme

1 Academic Year(s)

Total Credits for Programme

60

Exit Awards available

INSTITUTE INFORMATION

Teaching Institution

Queen's University Belfast

School/Department

Medicine, Dentistry and Biomedical Sciences

Quality Code
https://www.qaa.ac.uk/quality-code

Higher Education Credit Framework for England
https://www.qaa.ac.uk/quality-code/higher-education-credit-framework-for-england

Level 7

Subject Benchmark Statements
https://www.qaa.ac.uk/quality-code/subject-benchmark-statements

The Frameworks for Higher Education Qualifications of UK Degree-Awarding Bodies
https://www.qaa.ac.uk/docs/qaa/quality-code/qualifications-frameworks.pdf

N/A

Accreditations (PSRB)

REGULATION INFORMATION

Does the Programme have any approved exemptions from the University General Regulations
(Please see General Regulations)

No

Programme Specific Regulations

AWARDS, CREDITS AND PROGRESSION OF LEARNING OUTCOMES

The following regulations should be read in conjunction with the General Regulations of the University.

Students must pass all modules (60CATS) to be awarded the Certificate

Students with protected characteristics

N/A

Are students subject to Fitness to Practise Regulations

(Please see General Regulations)

No

EDUCATIONAL AIMS OF PROGRAMME

The aim of the programme is to provide a strong foundation in biostatistics and bioinformatics. Essential domain knowledge and context will be provided via an introduction to cell biology. Students will gain key, transferable, statistical, data analytical and scripting skills which will, in turn, provide a springboard into further specialist bioinformatics training and qualifications.

LEARNING OUTCOMES

Learning Outcomes: Cognitive Skills

On the completion of this course successful students will be able to:

Critically evaluate scientific literature.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Creatively apply and extend scientific principles to new problems.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Efficiently analyse and summarise core concepts from diverse sources.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Transferable Skills

On the completion of this course successful students will be able to:

Critical, analytical and creative thinking.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Oral communication and in writing scientific documentation

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Handling various types of IT resources.

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Time management

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Team work

Teaching/Learning Methods and Strategies

Online-based discussion, practical exercises

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Knowledge & Understanding

On the completion of this course successful students will be able to:

Communicate the principles of cell biology.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Perform statistical analyses and interpret the output from such analyses

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Explain basic principles of statistical methods.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise the basic elements of programming languages such as R

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Communicate the importance of data integration

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Explain the key concepts in health informatics and its integration with translational bioinformatics to facilitate the development of precision medicine approaches

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Learning Outcomes: Subject Specific

On the completion of this course successful students will be able to:

Select, apply and interpret statistical methods in the analysis of biomedical, omics and clinical data

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Interrogate relevant online resources for efficient data retrieval and analysis

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise comprehensive programming skills.

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

Utilise a variety of existing databases in biomedical research

Teaching/Learning Methods and Strategies

Online-Lectures, tutorials, practicals, self-directed learning

Methods of Assessment

Coursework, practical assignments

MODULE INFORMATION

Programme Requirements

Module Title

Module Code

Level/ stage

Credits

Availability

Duration

Pre-requisite

 

Assessment

 

 

 

 

S1

S2

 

 

Core

Option

Coursework %

Practical %

Examination %

Introductory Cell Biology & Computational analysis for Bioinformatics

SCM8159

7

10

YES

6 weeks

N

YES

100%

0%

0%

Health and Biomedical informatics and the exposome

SCM8148

7

10

YES

6 weeks

N

YES

100%

0%

0%

Biostatistical Informatics

SCM8109

7

20

YES

6 weeks

N

YES

100%

0%

0%

Scientific Programming & Statistical Computing

SCM7047

7

20

YES

YES

6 weeks

N

YES

100%

0%

0%

Notes