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DRPS : Course Catalogue : School of Biological Sciences : Postgraduate

Postgraduate Course: Practical Systems Biology (PGBI11089)

Course Outline
SchoolSchool of Biological Sciences CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryMolecular biology is being transformed by the recent invention of new technologies, particularly in genome sequencing and single-cell assays, and future research biologists will be expected to be as familiar with the computer as with the pipette. Systems biology is now a generic term to describe such quantitative approaches, particularly in cell and molecular biology. There, given that we know the sequence of all the genes in many organisms, the challenge is to understand how these genes interact, and functioning together as a system, produce the remarkable behaviours we associate with life.

This course will provide an introduction to systems biology by focusing on the behaviours expected from interactions between only a few genes, taking examples from microbes to mammals. Cells are dynamic systems, and we will build intuition about the types of responses expected from different gene ¿circuits¿ by running, adapting, and analysing computer simulations. Throughout, the course will use such simulations and analysis as research tools to understand biology. After an introduction to motifs and modules, we will focus on the role of feedback in genetic networks and how feedback can sometimes create permanent switches, in, for example, stem cells, or at other times can generate oscillations such as circadian rhythms in neurons. We will show how these behaviours can be undermined when numbers of molecules become low, an effect that cells may exploit or regulate away. Finally, we discuss experimental techniques that allow direct comparison between simulations and real biological systems.
Course description Week 1
Lectures 1 & 2: "What is systems biology?"

Week 2
Lectures 3 & 4: "Simulating a biomolecular network"

Week 3
Lectures 5 & 6: "Input-output and ultrasensitivity"

Week 4
Lecture 7 & 8: "Motifs, modules, and attractors"

Week 5
Lectures 9 & 10: "Positive feedback and genetic switches"

Week 6
Lectures 11 & 12: "Negative feedback to reduce response times"

Week 7
Lectures 13 & 14: "Negative feedback and oscillations"

Week 8
Lectures 15 & 16: ¿Circadian rhythms¿

Week 9
Lectures 17 & 18: ¿Stochastic gene expression¿

Week 10
Lectures 19 & 20: ¿Stochasticity and gene regulation¿

Week 11
Lecture 21 & 22: ¿Connecting models to experiments¿
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2015/16, Not available to visiting students (SS1) Quota:  46
Course Start Semester 1
Course Start Date 21/09/2015
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 22, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Two in-course assignments (25% each) and a research project (50%).

The assignments will involve working through a step-by-step computational analysis of a model of a biological system.

The aim of the research project is to demonstrate that the students are able to use computer simulation to test biological hypotheses.
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Students will gain an appreciation of how interactions between genes can explain some of the behaviour we see in cells.
  2. Students will gain an understanding of the different behaviours expected in dynamical systems and how to biochemically ¿code¿ for some of these behaviours.
  3. Students will develop skills in programming and simulation and learn how to use computers as tools to help decide between different hypotheses.
Reading List
An introduction to systems biology, U Alon (Chapman & Hall, 2006)

Primer on Python for scientific programming, HP Langtangen (Springer, 2009). Available online.

Python programming fundamentals, KD Lee (Springer, 2011). Available online.
Additional Information
Graduate Attributes and Skills Not entered
Course organiserProf Peter Swain
Tel: (0131 6)50 5451
Course secretaryMiss Emma Currie
Tel: (0131 6)50 8649
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