University of central lancashire



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Date of Course Approval: 21st January 2010

Response to conditions approved: March 2010

Approved to operate from:




UNIVERSITY OF CENTRAL LANCASHIRE



Programme Specification

This Programme Specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided.



Sources of information on the programme can be found in Section 17








  1. Awarding Institution / Body



University of Central Lancashire

  1. Teaching Institution and Location of Delivery



University of Central Lancashire

Preston campus



  1. University Department/Centre



Computing, Engineering and Physical Sciences

  1. External Accreditation






  1. Title of Final Award



BSc (Hons) Bioinformatics

BSc Bioinformatics



  1. Modes of Attendance offered



Full-time


  1. UCAS Code



CG94

  1. Relevant Subject Benchmarking Group(s)




Computing

Mathematics&Statistics

Biology


  1. Other external influences



British Computing Society (BCS)

  1. Date of production/revision of this form

Nov 2009

  1. Aims of the Programme




The recent completion of the Human Genome Project and the use of novel technologies such as DNA chips has revolutionised the life sciences, enabling the biological processes to be studied far more comprehensively than was previously possible. Laboratory-based research generates vast amount of data that requires novel bioinformatics approaches for its analysis, interpretation and storage.

The course will produce graduates with both a range of general transferable skills and a knowledge and understanding of Bioinformatics as a multidisciplinary subject, and will provide students with relevant interdisciplinary theoretical and practical skills for sustained and rewarding employment. In addition, the Bioinformatics/Computing Modules are highly vocational; students may apply their software development skills in other computer-related industries.



  • To develop an enquiring attitude and to encourage and enable students to become independent learners.

  • To develop competence in the implementation and monitoring of plans for self-development

  • To enable students to understand the major ideas and developments in Bioinformatics and related subjects

  • To develop the ability to understand and define clearly a problem and develop algorithms and computer programs for solving the problem both independently and as part of a team.

  • To develop the ability to analyse the results of computational analyses.

  • To enable the student to appreciate the value and limitations of computational methods used in bioinformatics analyses.

  • To develop communication skills.

  • To prepare the student for future employment in the biological, biomedical and pharmacological industries, teaching and research.

  • To provide the student with a suitable multidisciplinary body of knowledge as an appropriate basis for further professional development in a variety of science-based careers (including a higher degree e.g. MSc or PhD).



  1. Learning Outcomes, Teaching, Learning and Assessment Methods




A. Knowledge and Understanding

The successful student will be able to

A1. Describe and explain relevant principles and concepts of molecular biology.

A2. Demonstrate knowledge of fundamental principles of Computer Science, networking and program design.

A3. Explain, evaluate and apply a variety of bioinformatic/computational techniques.

A4. Design and implement software tools for analysis and storage of biological data.

A5. Solve biological problems using basic mathematical and statistical approaches.



Teaching and Learning Methods

Formal lectures, tutorials, workshops, discussion forums with peers.

Assessment methods

Essays, program development and evaluation, problem sheets, examinations, dissertation/project

B. Subject-specific skills

The successful student will be able to

B1. Write and modify algorithms and program to solve specific bioinformatic problems

B2. Design and query biological databases

B3. Design and implement a Web application

B4. Conduct scientific research using PC and/or Web-based software tools

B5. Critically evaluate scientific data and perform appropriate statistical tests to analyse data that will be produced by various types of study



Teaching and Learning Methods

Computational laboratory classes, workshops

Assessment methods

Program development and implementation, problem sheets, dissertation/project

C. Thinking Skills

The successful student will be able to

C1. Investigate computational aspects of complex biological problems

C2. Extract relevant information from journal articles, reviews and other sources of reference material (all Level 5 modules)

C3. Evaluate ideas, methods and systems

C4. Analyse and solve problems


Teaching and Learning Methods

Intellectual skills are developed through practical work, tutorial/seminars and coursework assignments. Discussion among students and with staff during tutorials and supervisory meetings are key methods for the development of thinking skills. Problem-solving is developed in practical classes, seminars and tutorials. Throughout the course, students practise problem-solving individually and in groups. Students research, apply and evaluate information during the Bioinformatics-related modules, Case Studies and during the problem-solving project.

Assessment methods

Staff in class and in supervisory meetings provides informal feedback. Intellectual skills are partly assessed through formal examinations but assessment of coursework, practical and theoretical project work is the main vehicle for assessment of the higher order skills. A variety of assessment methods are used, including formal reports, essays, and poster presentations.

D. Other skills relevant to employability and personal development

The successful student will be able to

D1. Write using an appropriate scientific writing style that would be acceptable to an informed reader in the relevant areas of study.

D2. Communicate ideas and conclusions effectively to a scientific audience.

D3. Learn and work independently and as part of a team

D4. Operate within an appropriate ethical and legal framework

D5. Plan, perform, manage and report on a relevant project

D6. Identify and set personal goals relevant to long-term educational and career planning


Teaching and Learning Methods

The development of essential communication and transferable skills begins in the Bioinformatics I module at level L4, alongside the introduction and discussion of relevant legal and ethical topics. Communication skills, legal and ethical understanding are further developed in context in other modules through tutorial/seminar work and coursework assignments. Teamwork is developed in the Bioinformatics modules (CO1808-L4, CO2516-L5) and Case Studies (CO2518-L5) module. An individual project (CO3808-L6), supported by supervisory meetings, reinforces and extends the student’s abilities to research topics relevant to their project, to write a paper summarising and evaluating their findings, to plan and monitor their progress, solve problems and write an extended report.


Assessment methods

These skills are assessed through written coursework in many modules, but particularly the Case Studies project and the final year individual project, where students write a project report, are interviewed, and give a poster presentation.




13. Programme Structures*


14. Awards and Credits*

Level

Module Code

Module Title

Credit rating

Level 6

CO3808

CO3811
CO3812

CO3813

CO3402


Honours Degree Project

Machine Learning and Data Mining

Bioinformatics for ‘omics (transcriptomics, proteomics, metabolomics)

Biostatistics and SPSS

Object-oriented Methods in Computing


40
20

20

20


20

Bachelor Honours Degree in Bioinformatics

Requires 360 credits including a minimum of 240 at Level 5 or above and 100 at Level 6.


Bachelor Degree in Bioinformatics

Requires 320 credits including a minimum of 200 at Level 5 or above and 40 at Level 6.


Diploma of Higher Education in Bioinformatics

Requires 240 credits including a minimum of 100 at Level 5 or above. It must include at least two of the following modules: CO1808, CO2516, CO3812 and CO3813; otherwise the title will be Diploma of Higher Education.


Certificate of Higher Education in Bioinformatics

Requires 120 credits at Level 4 or above. It must include at least one of the following modules: CO1808, CO1809 or CO2516; otherwise the title will be Certificate of Higher Education.




Level 5

CO2516

CO2701


CO2402

CO2517


CO2518
CO2519


Bioinformatics II

Database Systems

Advanced Programming

Mathematics and Statistics

Case Studies in Bioinformatics and Biostatistics

Biomolecular Structure and Dynamics



20

20

20



20
20
20

Level 4

CO1404
CO1401

CO1505


MA1051

CO1809


CO1808

CO1810



Introduction to Software Development.

Program Design & Implementation

Computing Skills

Foundation Mathematics

Fundamentals of Computers, Networking and BioPerl Programming

Bioinformatics I

Basic Molecular Biology and Genetics

10

10



20

20

20



20
20




15. Personal Development Planning


Students are able to engage in PDP during many of the taught modules. PDP activities are also conducted through meetings with their Course Leader/Personal Tutors. In these sessions students identify past skills, evaluate new skills and consider long-term goal setting and link PDP with employability and enterprise. Case Studies module (CO2518) and the project module CO3808 give opportunities to explore project management skills and evaluate performance.

Meetings with project supervisors allow the students to identify areas of strength and weakness and to develop appropriately. It provides an opportunity to investigate an area relevant to career goals.

In addition, students can undertake a semester-based University Employability Certificate. This enhances the students’ self-awareness and ability to seek employment particularly within computing. Students gain a separate University Certificate in addition to their Degree.


16. Admissions criteria

Programme Specifications include minimum entry requirements, including academic qualifications, together with appropriate experience and skills required for entry to study. These criteria may be expressed as a range rather than a specific grade. Amendments to entry requirements may have been made after these documents were published and you should consult the University’s website for the most up to date information.



Students will be informed of their personal minimum entry criteria in their offer letter.


Two A2 Levels at Grade ‘B’ in a science, maths or computing related subject is expected, plus 5 GCSE’s (including both mathematics and English at Grade ‘C’ or above) or equivalent.


17. Key sources of information about the programme


  • School Web Site (www.uclan.ac.uk/computing)

  • Student Handbook




18. Curriculum Skills Map

Please tick in the relevant boxes where individual Programme Learning Outcomes are being assessed

Level

Module Code

Module Title

Core (C), Compulsory (COMP) or Option (O)

Programme Learning Outcomes

Knowledge and understanding

Subject-specific Skills

Thinking Skills

Other skills relevant to employability and personal development













A1

A2

A3

A4

A5

B1

B2

B3

B4

B5

C1

C2

C3

C4

D1

D2

D3

D4

D5

D6

LEVEL 6

CO3808

Honours Degree Project

C











































CO3811

Machine Learning and Data Mining

COMP





















































CO3812

Bioinformatics for ‘omics (transcriptomics, proteomics, metabolomics)

C



















































CO3813

Biostatistics and SPSS

COMP




















































CO3402

Object-oriented Methods in Computing

COMP

























































LEVEL 5

CO2516

Bioinformatics II

C

















































CO2701

Database Systems

COMP






















































CO2517

Mathematics and Statistics

COMP
























































CO2518

Case Studies in Bioinformatics and Biostatistics

COMP










































CO2519

Biomolecular Structure and Dynamics

COMP



















































CO2402

Advanced Programming

COMP




















































LEVEL 4

CO1404

Introduction to Software Development

COMP




















































CO1401

Program Design and Implementation

COMP




















































CO1505

Computing Skills

COMP





















































MA1051

Foundation Mathematics 1

COMP



























































CO1809


Fundamentals of Computers, Networking and BioPerl Programming

C

















































CO1808

Bioinformatics I

C
















































CO1810

Basic Molecular Biology and Genetics

COMP





















































Note: Mapping to other external frameworks, e.g. professional/statutory bodies, will be included within Student Course Handbooks

Updated: September 13




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