Undergraduate Course: Bioinformatics 1 (INFR11160)
Course Outline
| School | School of Informatics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Year 4 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This is an introductory course for the discipline of Bioinformatics for students from both physical science and life science backgrounds. Bioinformatics is an inter-disciplinary subject that develops and implements novel methodologies and tools for analysing and learning from biological data. These data are increasingly large and complex because of significant technological developments and their application at scale in biological and biomedical application areas.
In this course, we will cover the fundamental domain knowledge needed from both biological and computational disciplines to enable further study and research in this subject with a strong emphasis on practical applications of the taught methods. |
| Course description |
In this course, we will introduce key biological concepts including the main types of molecules we study (DNA, RNA, and protein) and the cell biological processes involved in the regulation and function of biological systems. The cornerstone of foundational Bioinformatics lies in the analysis of sequences; strings of characters that encode genetic information in organisms. We will describe the theory and put into practice how we work with and analyse these sequences using a range of databases, algorithms, and tools. You will undertake mini research projects using publicly available data to put your learning into practice. The course is taught using Python; students need to be comfortable with basic coding in Python as this is required to use the course notebooks each week and for the assessed coursework.
Topics change slightly each year, but typically include:
pairwise and multiple sequence alignment, biological databases, ontologies & functional enrichment analysis, network analysis, multi-omics analysis (transcriptomics, proteomics, methylomics), and biomedical text analytics.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
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. |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2023/24, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
| Course Start Date |
18/09/2023 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 10,
Supervised Practical/Workshop/Studio Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
78 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
This course will be assessed by two major pieces of coursework. |
| Feedback |
Students will receive written feedback from markers for each piece of coursework. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- communicate between biological and computational domains to facilitate effective inter-disciplinary working
- use and / or implement Bioinformatics tools, services, and software in practical research
- have sufficient background knowledge, skills and understanding to discover and apply additional bioinformatics techniques in future work
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Reading List
The course will have a dedicated University Resource List. If students would like to look through the key textbook for the course in advance it can be read online for free from the University e-book library:
Pevsner, J., 2015. Bioinformatics and functional genomics Third., Hoboken: John Wiley & Sons, Incorporated. https://discovered.ed.ac.uk/permalink/f/gfso8q/44UOE_ALMA51221474230002466 |
Additional Information
| Graduate Attributes and Skills |
problem-solving, critical / analytical thinking, knowledge integration, cross-disciplinary communication. |
| Keywords | BIO1,bioinformatics,computational biology,biological informatics |
Contacts
| Course organiser | Dr Ian Simpson
Tel: (0131 6)50 2747
Email: |
Course secretary | Miss Yesica Marco Azorin
Tel: (0131 6)505113
Email: |
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