Learning, Teaching and Quality Committee
PROGRAMME SPECIFICATION FOR
AWARDS MADE BY THE UNIVERSITY OF EAST ANGLIA
SECTION A: SESSION: 2012 to 2013
A1
Course Name
Computational Biology
A2
MSc
A3
Final Award
(e.g. BA/BSc(Hons)/
MA/MSc etc)
UEA Course Code(s)
A4
UCAS Course Code(s)
A5
Professional Award
(if any)
None
A6
School of Studies
School of Computing Sciences
T1CG15102, T2CG15202, T2CG15402
SECTION B: SUMMARY OF COURSE STRUCTURE AND FEATURES
B1
Summary
e.g. General statement about course structure, including special features such as placement
opportunities, whether these are compulsory or optional; fieldwork; year abroad. Include any
cross references to other relevant information such as Student Handbook and/or School/Faculty
website.
This course is aimed at developing computer skills, to produce scientists that are able to design and
implement their own software to address problems in Computational Biology as well as to
understand and use existing and commonly used software suites.
Rationale
 To aid biology graduates to develop computer skills and a deeper understanding of
fundamentals of the computational sciences as applied to biology.
 To address a national shortage of trained computational biologists.
1
Philosophy
This programme’s philosophy is to deepen the student’s knowledge of the problems and methods
used in the broad area of Computational Biology and to develop their understanding and computer
skills such that they are able to design and implement their own methods. It is also to provide
them with knowledge and experience of the important tools and databases that are in common
usage by Computational Biologists. This makes considerable intellectual demands on students,
most obviously in the manner and pace of teaching, that relies on the additional intellectual and
emotional maturity expected of a graduate.
Structure of the course
The full-time course is divided into two parts:
Taught modules: September to May. Students take compulsory modules which are primarily
designed to provide a coherent foundation and a deep appreciation of all the main areas of
Computational Biology.
Dissertation: May to September. The dissertation project draws on the material from many
taught modules and beyond; students are typically required to integrate a wide range of
knowledge and skills. It is often undertaken in one of the Norwich Research Park biological
institutes. This course can also be taken part-time over 2 or 3 years following the profile
outlined in section D1.
Knowledge and understanding
 Relating to modern computational theory and practice as applied to biology (a-b);
 of algorithms used and their application to problems in Computational Biology (c);
 of appropriate problem solving strategies (d);
 of commercial, professional, legal and ethical issues (e-g);
 of a variety of symbolic notations (h);
Cognitive skills
 reason and make professional judgements (a-b);
 problem solving (c);
 formulate and test hypotheses (d)
 manage research (e);
Subject specific skills
 bridge disciplines (a);
 design and implementations of software (b);
 evaluate and analyse biological data (c);
 using symbolic notations (d);
Key skills
 self management (a);
 communication skills (b);
 team working (c);
 IT skills (d);
 professional development (e);
SECTION C: EDUCATIONAL AIMS AND OUTCOMES
2
C1
Educational Aims of the Programme
(Include any distinctive/innovative features/route pathways)
The MSc Computational Biology is a 12 month full-time course which may also be taken part-time over 2 or 3
years. It is designed for applicants with a first degree in Biology or any Science/Engineering discipline, or
applicants with equivalent qualifications and experience, wishing to broaden, deepen or update their skills and
knowledge in Computational Biology. Its aims are to:

Provide a high quality postgraduate programme of advanced study which combines intellectual
challenge and relevance to current issues in Computational Biology.
 Maintain the central role of research to inform teaching and to engage students in the critical
review of new developments in the field.
 Further develop in students the intellectual skills of reasoning, problem-solving, self-expression,
and independent research thereby enabling them to deal with complex issues both systematically
and creatively.
 Foster commitment to and enthusiasm for Computational Biology; to prepare students for a
career furthering these interests and to engender in the most able students a desire to engage in
doctorial research.
 Prepare students for a career furthering these interests, either directly, as a career change, or in
conjunction with their prior knowledge.
C2 Course Outcomes
C2(i) Knowledge and understanding
Teaching/learning methods and strategies
a Systematic understanding of software design and
implementation, especially the integration of a range of
techniques to solve practical biological problems;
Teaching is formally divided into lectures, practical
classes for timetabling purposes, but within these
slots there is a lot of flexibility. For example,
although many lectures use traditional methods of
slides and commentary, many also include
discussions, demonstrations, computer
demonstrations etc. Practical class timetable slots
in computing are used for assistance with
programming exercises. Seminars, visiting
lecturers from Industry, and directed reading, in
addition to more traditional practical exercises are
also used. Directed student-centered learning is
encouraged using WWW, library and other
facilities.
b In depth knowledge of existing software and databases
that are used by computational biologists.
c Critical assessment and understanding of the scientific
basis of computational models used in biology and their
application to relevant software and databases.
d A systematic approach to analysing and solving
problems using a range of appropriate strategies and
specific techniques.
Assessment
e Recognition and evaluation of the interplay between
social and technological developments in Computational
Biology
f In depth understanding of professional and legal
issues, especially ethical and intellectual property rights.
g Critical assessment and understanding of relevant
academic, commercial and marketing literature.
h Knowledge of a variety of symbolic notations,
particularly computer programming languages and
diagrammatic formalisms for problem and software
specification and design
3
 Coursework includes programming exercises, use
of well established Computational Biology software
tools (e.g. BLAST, homology modelling software),
essays, etc. Knowledge and understanding are
assessed on the basis of reports and demonstrations.
C2(ii) Cognitive Skills
Teaching/learning methods and strategies
a Formulate ill-defined problems into well-defined
projects.
b Apply numerical and reasoning skills and critically
review different approaches to problems.
c Solve complex problems and make decisions in new
situations.
d Frame hypothesis, test theory with observations and
evaluate diverse data relating to real world problems.
e Ability to undertake research and experimental design,
showing independence of thought and judgement.
Intellectual skills are developed by direct contact
with lecturers. Throughout the programme,
modules involve applied work in collecting,
analysing or reviewing data and observations, with
particular emphasis on the critical assessment of
existing knowledge. Reasoning skills, problem
posing and solving skills are promoted through
seminars and groups discussions. Some exercises
are well defined and focused on a particular
technique or skill; others are less well defined and
the student has to refine the project and determine
(and justify) the best approach. In all cases results
have to be presented clearly and analysed.
Research, design and analysis are brought together
in the dissertation, which normally has a substantial
practical component and requires the integration of
skills and knowledge from several parts of the
 programme.
Assessment
Intellectual skills are assessed variously through the
design and implementation of computer programs,
essays, reports, presentations and problem sheets.
Intellectual skills are formally indentified in
assessment guidelines, made available to students.
Problem solving and reasoning skills are
fundamental to many assessed exercises.
The requirement to produce a dissertation, of c.
15,000 words, allows assessment at the highest
level of intellectual skills acquired and integrates
much of the material taught in other parts of the
student’s course.
C2(iii) Subject Specific Practical Skills
Teaching/Learning methods and strategies
a Ability to combine knowledge and understanding from
the two different disciplines and creatively solve
problems in new situations.
Lectures are the general vehicle for introducing the
basics of a topic, which are supplemented by
directed reading, seminars, and laboratories where
appropriate. Practically oriented modules will often
use supervised laboratories for supporting
development of computer programs. Modules
which address more theoretical and abstract
concerns often use seminars to exemplify and
amplify the ideas and notations used in lectures,
and stimulate discussion of topics.
b Self direction and originality in problem identification
and analysis, and in the design and implementation of
software that addresses problems in biology.
c Ability to evaluate and analyse biological data from a
variety of sources and research conclusions based on
scientific understanding.
4
d Competence in handling a variety of symbolic
notations, including programming languages and
diagrammatic formalisms.
Assessment
Problem analysis, program design and
implementation are typically assessed by
coursework exercises and through demonstration of
their operation. Competence with specific
 notations, the underlying methodologies of
research, design and implementation of programs,
and comparative attributes of existing systems are
usually assessed by a combination of seminar
performance, coursework exercises and
examination.
C2(iv) Key Skills and Attributes
Teaching/Learning methods and strategies
a Think and work independently, integrate knowledge
and problem-solving strategies, exercise own judgement,
deal with unfamiliar situations and manage own time.
Transferable skills training is a compulsory part of
the first semester programme; it is the focus of
much of the compulsory Research Methods
module. Coursework in many modules entails
presentation skills. Seminars rely on discussion
and interaction, often focussed around reading
particular papers. Independent work is required in
the majority of coursework, in the dissertation and
in examinations.
b Retrieve and synthesise information from independent
sources and present coherent intellectual arguments in
oral, written, and graphical form, suitably referenced and
formatted for both specialist and non-specialist audiences.
c Work effectively as part of a team.
d Make full use of information technology: e-mail, word
processing, the web, software development tools etc.
e Recognition of the importance of continuous
professional development and appropriate standards of
behaviour.
5
Assessment
Assessment of skill is a fundamental aspect of most
work on the programme. Other transferable skills
are less amenable to direct assessment but
submission of word-processed assignments on time
and to a satisfactory standard confirms that skills
 have been acquired.
SECTION D1: COURSE PROFILE AND AWARD REQUIREMENTS
Please insert (i.e. cut and paste) the course profile here or complete the following boxes, as appropriate. If
you insert the course profile, please ensure that the NOTICE below about changes to modules is retained.
Each box relates to a year of study. If the programme is part-time or offers a part-time option, please extend
the number of years as appropriate (maximum = 9).
NOTICE: Whilst the University will make every effort to offer the modules listed, changes may
sometimes have to be made for reasons outside the University’s control (e.g. illness of a member of staff)
or because of low enrolment numbers or sabbatical leave. Where this is the case, the University will
endeavour to inform students.
Core, Compulsory and Optional modules
Progression requirements or
See attached course profile
Award
60 credits
[PG Cert.]
Year 1
120 credits
[PG Dip.]
180 credits
MSc Computational Biology
6
2 and 4 year Part-time
See attached course profile
60 credits
[PG Cert.]
120 credits
[PG Dip.]
180 credits
MSc Computational Biology
7
SECTION D2: REGULATORY FRAMEWORK FOR AWARDS
D2a Regulatory Framework: (please tick against the relevant framework)
Common Course Structure for Undergraduate Programmes (CCS)
NAM Common Course Structure (NAM-CCS)

Common Regulatory Framework for Postgraduate Programmes (CPG)
It is expected that all new degree courses will conform to the common University regulations
(either to CCS, NAM-CCS or CPG, and the associated Instructions to Examiners).
D2b Degree Classifications
For First degree programmes
i)
Weighting (in percentage terms) which each year of the course contributes to the
calculation of the degree classification.
(Part-time Programmes)
Year 1
Year 5
Year 2
Year 6
Year 3
Year 7
Year 4
Year 8
Year 9
ii)
Please indicate whether an aggregate mark and/or the University marks profile is taken into
consideration for the purpose of determining degree class.
D2c Postgraduate Awards
i)
Are (any)s assessed on a pass/fail (instead of numerical) basis?
YES
NO

If so how many credits are assessed on a pass/fail basis
ii)
Can the award be conferred with distinction?
iii)
On what criteria is the distinction awarded? (See
also the Regulations for the Common
Postgraduate Regulatory Framework.)
8
…………
YES

NO
An aggregate over 180 credits of at
least 70%
APPENDIX A - COURSE PROFILE
FULL TIME ONE YEAR
Course Profile for 2012/3
Course:
Computational Biology (Msc) (T1CG15102)
School:
Computing Sciences
Director:
Dr Katharina Huber
Year 1
Compulsory Modules (130 credits)
Module
Description
Assessment Credits Period Sub-slot
CMPSMP6X DISSERTATION
DS
60
SEM2 U
FUNDAMENTALS OF
CMPSMB4Y COMPUTATIONAL AND
STRUCTURAL GENOMICS
CW
30
YEAR C6*E5,C3*D4
CMPSMP2Y RESEARCH TECHNIQUES
CW
20
YEAR D5*D6,D8*B9/E1*E2
CMPSMB38 GENOME INFORMATICS
CW
20
SEM2 U
Options Range A
BIOLOGY Stream students MUST take CMPSMA23, CMPSMB11 and CMPSMC32. COMPUTING Stream
students MUST take CMPSMC24 and BIO-M109, they must ALSO choose one module from CMPSMB13,
CMPSMB29 or CMPSMA23.
Students will select 50 credits from the following modules:
Module
Description
Assessment Credits Period Sub-slot
BIO-M109
"GENETICS, GENOMICS AND
BIOINFORMATICS"
CW
10
SEM1 BS
CMPSMA23 APPLICATIONS PROGRAMMING
CW
20
SEM1 B1*B2,B3*E4
CMPSMB11 DATABASE MANIPULATION
WW
20
SEM1 A5*A6,A7/B6,B7*B8
CW
20
SEM1 A1*A2,D3*C4
CMPSMB29 INFORMATION RETRIEVAL
CW
20
SEM1 E1*E2,A7*A8
CMPSMC24 DATA MINING
CW
20
SEM2 B2*D7*D8,C1*C2
WW
10
SEM2 B1*B2,B5*B8,A5*A6
CMPSMB13
CMPSMC32
INTERNET & MULTIMEDIA
TECHNIQUES
MATHEMATICS AND ALGORITHMS
FOR COMPUTATIONAL BIOLOGY
9
PART-TIME TWO YEARS
Course Profile for 2012/3
Course:
Computational Biology (Msc) (T2CG15202)
School:
Computing Sciences
Director:
Dr Katharina Huber
Year 1
This is the first year of your Taught Masters Programme
Compulsory Modules ( 50 credits)
Module
Description
Assessment
Credits
Period
Sub-slot
CMPSMB4Y
FUNDAMENTALS OF
COMPUTATIONAL AND STRUCTURAL
GENOMICS
CW
30
YEAR
C6*E5,C3*D4
CMPSMB38
GENOME INFORMATICS
CW
20
SEM2
U
Options Range A
BIOLOGY Stream students MUST take CMPSMA23 and CMPSMC32. COMPUTING Stream students
MUST take CMPSMC24 and BIO-M109.
Students will select 30 credits from the following modules:
Module
Description
Assessment Credits Period Sub-slot
BIO-M109
"GENETICS, GENOMICS AND
BIOINFORMATICS"
CW
10
SEM1 BS
CMPSMA23 APPLICATIONS PROGRAMMING
CW
20
SEM1 B1*B2,B3*E4
CMPSMC24 DATA MINING
CW
20
SEM2 B2*D7*D8,C1*C2
WW
10
SEM2 B1*B2,B5*B8,A5*A6
CMPSMC32
MATHEMATICS AND ALGORITHMS
FOR COMPUTATIONAL BIOLOGY
This is the second year of your Taught Masters Programme
Compulsory Modules ( 80 credits)
Module
Description
Assessment Credits Period Sub-slot
CMPSMP6X DISSERTATION
DS
60
SEM2 U
CMPSMP2Y RESEARCH TECHNIQUES
CW
20
YEAR D5*D6,D8*B9/E1*E2
Options Range A
BIOLOGY Stream students MUST take CMPSMB11. COMPUTING Stream students MUST choose one
module from CMPSMB13, CMPSMB29 or CMPSMA23.
Students will select 20 credits from the following modules:
Module
Description
Assessment Credits Period Sub-slot
CMPSMA23 APPLICATIONS PROGRAMMING
CW
20
SEM1 B1*B2,B3*E4
CMPSMB11 DATABASE MANIPULATION
WW
20
SEM1 A5*A6,A7/B6,B7*B8
CW
20
SEM1 A1*A2,D3*C4
CW
20
SEM1 E1*E2,A7*A8
CMPSMB13
INTERNET & MULTIMEDIA
TECHNIQUES
CMPSMB29 INFORMATION RETRIEVAL
PART-TIME FOUR YEARS
10
Course Profile for 2012/3
Course:
Computational Biology (Msc) (T2CG15402)
School:
Computing Sciences
Director:
Dr Katharina Huber
This is the 1st Year of your Taught Masters Programme.
Options Range A
BIOLOGY Stream students MUST take CMPSMA23 only. COMPUTING Stream students MUST take
CMPSMC24 and BIO-M109.
Students will select 30 credits from the following modules:
Module
Description
Assessment Credits Period Sub-slot
BIO-M109
"GENETICS, GENOMICS AND
BIOINFORMATICS"
CW
10
SEM1 BS
CMPSMA23 APPLICATIONS PROGRAMMING
CW
20
SEM1 B1*B2,B3*E4
CMPSMC24 DATA MINING
CW
20
SEM2 B2*D7*D8,C1*C2
WW
10
SEM2 B1*B2,B5*B8,A5*A6
CMPSMC32
MATHEMATICS AND ALGORITHMS
FOR COMPUTATIONAL BIOLOGY
This is the 2nd Year of your Taught Masters Programme.
Compulsory Modules ( 30 credits)
Module
Description
Assessment
Credits
Period
Sub-slot
CMPSMB4Y
FUNDAMENTALS OF
COMPUTATIONAL AND STRUCTURAL
GENOMICS
CW
30
YEAR
C6*E5,C3*D4
Options Range A
BIOLOGY Stream students MUST take CMPSMB11. COMPUTING Stream students MUST choose one
module from CMPSMB13, CMPSMB29 or CMPSMA23.
Students will select 20 credits from the following modules:
Module
Description
Assessment Credits Period Sub-slot
CMPSMA23 APPLICATIONS PROGRAMMING
CW
20
SEM1 B1*B2,B3*E4
CMPSMB11 DATABASE MANIPULATION
WW
20
SEM1 A5*A6,A7/B6,B7*B8
CW
20
SEM1 A1*A2,D3*C4
CW
20
SEM1 E1*E2,A7*A8
CMPSMB13
INTERNET & MULTIMEDIA
TECHNIQUES
CMPSMB29 INFORMATION RETRIEVAL
This is the 3rd Year of your Taught Masters Programme
Compulsory Modules ( 40 credits)
Module
Description
Assessment Credits Period Sub-slot
CMPSMP2
Y
RESEARCH TECHNIQUES
CW
20
YEAR D5*D6,D8*B9/E1*E2
CW
20
SEM2 U
CMPSMB38 GENOME INFORMATICS
This is the 4th Year of your Taught Masters Programme.
Compulsory Modules ( 60 credits)
Module
Description
Assessment
11
Credits
Period
Sub-slot
CMPSMP6X
DISSERTATION
DS
12
60
SEM2
U