Postgraduate Course: Bioinformatics 2 (INFR11005)
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://course.inf.ed.ac.uk/bio2 |
Taught in Gaelic? | No |
| Course description | Bioinformatics is at the interface between two of the most influential scientific fields. An appreciation of computational and biological sciences, in particular the terminology employed in both fields, is essential for those working at such an interface. In this course, we aim to cover the following:
* The concepts of computer science that relate to problems in biological sciences.
* Commercial and academic perspectives on bioinformatics.
* The impact of bioinformatics on the methodologies used in biological science.
* The influence biological science has on computing science. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Bioinformatics 1 (INFR11016)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.
This course assumes some mathematics at the level of undergraduate computer science, including:
- Probability theory, particularly discrete random variables;
- Some (very basic) statistics
No specific programming is taught or required, but students should be familiar with using software packages and will be required to use some packages in R for the lab/assignment. |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | Yes |
Course Delivery Information
|
| Delivery period: 2013/14 Semester 2, Available to all students (SV1)
|
Learn enabled: No |
Quota: None |
|
Web Timetable |
Web Timetable |
| Course Start Date |
13/01/2014 |
| Breakdown of Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 020,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
76 )
|
| Additional Notes |
|
| Breakdown of Assessment Methods (Further Info) |
Written Exam
70 %,
Coursework
30 %,
Practical Exam
0 %
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | | 2:00 | |
Summary of Intended Learning Outcomes
1 - Describe the main computational algorithms used in the analysis of biological sequences
2 - Discuss the practical limitations of sequence analysis methods and contrast the methods available
3 - Appraise common biological data sources and the key contributing error/noise sources in such data
4 - Demonstrate an understanding of how experimental design in biology is critical to subsequent data analysis and representation in bioinformatics
5 - Critically evaluate research literature in the field |
Assessment Information
Written Examination 70
Assessed Assignments 30
Oral Presentations 0
Assessment
Coursework will be assessed through a mini project exploring a research area of bioinformatics.
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 |
The course will cover the following:
* What is Bioinformatics?
* Pairwise and Multiple sequence alignment algorithms.
* Heuristic alignment algorithms and high throughput strategies.
* Identification and clustering of protein families and domain families.
* Phylogenetic reconstruction.
* Gene identification and annotation strategies in genomics.
* Sources of error in biological data and data provenance.
* Analysis of gene expression data.
* The future of bioinformatics: proteomics, neuroinformatics, e-science.
Relevant QAA Computing Curriculum Sections: Data Structures and Algorithms, Developing Technologies |
| Transferable skills |
Not entered |
| Reading list |
An Introduction to Bioinformatics Algorithms, Jones & Pevzner, MIT Press. |
| Study Abroad |
Not entered |
| Study Pattern |
Lectures 20
Tutorials 0
Timetabled Laboratories 0
Non-timetabled assessed assignments 30
Private Study/Other 50
Total 100 |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Iain Murray
Tel: (0131 6)51 9078
Email: I.Murray@ed.ac.uk |
Course secretary | Ms Katey Lee
Tel: (0131 6)50 2701
Email: Katey.Lee@ed.ac.uk |
|
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