Postgraduate Course: Models and Languages for Computational Systems Biology (INFR11047)
Course Outline
| School |
School of Informatics |
College |
College of Science and Engineering |
| Course type |
Standard |
Availability |
Available to all students |
| Credit level (Normal year taken) |
SCQF Level 11 (Postgraduate) |
Credits |
10 |
| Home subject area |
Informatics |
Other subject area |
None |
| Course website |
http://www.inf.ed.ac.uk/teaching/courses/mlcsb
|
Taught in Gaelic? |
No |
| Course description |
In this course we explore a range of modelling methods for pathways in molecular biology: whether metabolic, signalling, regulatory or transcriptional. These models draw on a rich existing theory of concurrent computational systems, with Petri nets as a unifying basic concept. Techniques range over qualitative and quantitative, discrete and continuous, differential and stochastic models. Working with these models, we look at logics for specifying and characterizing systems' behaviour. Finally, we investigate language-based approaches to modular description and analysis of systems, studying some computationally-inspired biological process calculi. |
Entry Requirements
| Pre-requisites |
|
Co-requisites |
It is RECOMMENDED that students also take
Computational Systems Biology (INFR11039)
|
| Prohibited Combinations |
|
Other requirements |
For Informatics PG and final year MInf students only, or by special permission of the School. Some logic and probability theory. General computer science education.
|
| Additional Costs |
None |
Information for Visiting Students
| Pre-requisites |
None |
| Displayed in Visiting Students Prospectus? |
Yes |
Course Delivery Information
|
| Delivery period: 2010/11 Semester 2, Available to all students (SV1)
|
WebCT enabled: No |
Quota: None |
| Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
| Central | Lecture | | 1-11 | | | | 16:10 - 17:00 | | | Central | Lecture | | 1-11 | 16:10 - 17:00 | | | | |
| First Class |
Week 1, Monday, 16:10 - 17:00, Zone: Central. Room 4.18, David Hume Tower |
| Exam Information |
| Exam Diet |
Paper Name |
Hours:Minutes |
Stationery Requirements |
Comments |
| Main Exam Diet S2 (April/May) | | 2:00 | 12 sides | |
Summary of Intended Learning Outcomes
1 - Describe different ways in which cellular pathways can be modelled, and explain advantages and disadvantages of each.
2 - Model simple pathways using a variety of methods.
3 - Program biological pathways of moderate complexity in a modular way, and employ current tools for their analysis.
4 - Describe process algebra formalisms proposed for modular biological modelling and their comparative advantages and disadvantages.
5 - Read, explore and use the literature on computational modelling in Systems Biology. |
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0
Assessment
There is a single exam paper at the end of the year, accounting for 70% of the course mark. In addition, there are two pieces of assessed coursework during the semester, worth 15% each, which require the modelling and analysis of biological pathways.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year. |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
* Petri nets: static and dynamic specification; matrix invariants; quantitative variants; biological interpretation and applications.
* Temporal logic: analysis of behavioural properties for biological networks; linear and branching-time logics; model-checking; discrete, stochastic and continuous variants.
* Markov systems: probabilities, discrete and continuous; Poisson and exponential distributions; Markov processes; continuous-time Markov chains; master equation and links between differential and stochastic approaches.
* Stochastic simulation: Gillespie algorithm; modifications; precision/cost trade-offs; relevant tools.
* Language-based approaches: biologically-inspired process calculi; modularity and scaling; computational tools.
Relevant QAA Computing Curriculum Sections: Data Structures and Algorithms, Developing Technologies |
| Transferable skills |
Not entered |
| Reading list |
Not yet available |
| Study Abroad |
Not entered |
| Study Pattern |
Lectures 20
Tutorials 0
Timetabled Laboratories 0
Non-timetabled assessed assignments 24
Private Study/Other 56
Total 100 |
| Keywords |
Not entered |
Contacts
| Course organiser |
Dr Michael Rovatsos
Tel: (0131 6)51 3263
Email: mrovatso@inf.ed.ac.uk |
Course secretary |
Miss Kate Weston
Tel: (0131 6)50 2701
Email: Kate.Weston@ed.ac.uk |
|
copyright 2011 The University of Edinburgh -
31 January 2011 7:53 am
|
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