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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2011/2012
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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Models and Languages for Computational Systems Biology (INFR11047)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits10
Home subject areaInformatics Other subject areaNone
Course website http://www.inf.ed.ac.uk/teaching/courses/mlcsb Taught in Gaelic?No
Course descriptionIn 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 (not applicable to Visiting Students)
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-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2011/12 Semester 2, Available to all students (SV1) WebCT enabled:  No Quota:  None
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
CentralLecture1-11 16:10 - 17:00
CentralLecture1-11 16:10 - 17:00
First Class Week 1, Monday, 16:10 - 17:00, Zone: Central. AT M1
No Exam Information
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
KeywordsNot entered
Contacts
Course organiserDr Michael Rovatsos
Tel: (0131 6)51 3263
Email: mrovatso@inf.ed.ac.uk
Course secretaryMiss Kate Weston
Tel: (0131 6)50 2701
Email: Kate.Weston@ed.ac.uk
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© Copyright 2011 The University of Edinburgh - 16 January 2012 6:17 am