Postgraduate Course: Bioinformatics 2 (INFR11005)
|School||School of Informatics
||College||College of Science and Engineering
||Availability||Available to all students
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
|Home subject area||Informatics
||Other subject area||None
||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)
|| Students MUST have passed:
Bioinformatics 1 (INFR11016)
|Prohibited Combinations|| Students MUST NOT also be taking
Bioinformatics 2 (20 points) (ARIN11005)
||Other requirements|| For Informatics PG and final year MInf students only, or by special permission of the School. This course assumes an undergraduate degree in computing or mathematical sciences. However, it would also be suitable for an individual from biological sciences with some programming experience.
|Additional Costs|| None
Information for Visiting Students
|Displayed in Visiting Students Prospectus?||Yes
Course Delivery Information
|Delivery period: 2011/12 Semester 2, Available to all students (SV1)
||WebCT enabled: No
|Central||Lecture||1-11|| 11:10 - 13:00|
||Week 1, Wednesday, 11:10 - 13:00, Zone: Central. George Sq 07 S37 |
|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
|Written Examination 70|
Assessed Assignments 30
Oral Presentations 0
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.
||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
||An Introduction to Bioinformatics Algorithms, Jones & Pevzner, MIT Press.
Timetabled Laboratories 0
Non-timetabled assessed assignments 30
Private Study/Other 50
|Course organiser||Dr Michael Rovatsos
Tel: (0131 6)51 3263
|Course secretary||Miss Kate Weston
Tel: (0131 6)50 2701
© Copyright 2011 The University of Edinburgh - 16 January 2012 6:17 am