Undergraduate Course: Genomics and Proteomics 2 (IBMS08014)
Course Outline
| School | Deanery of Biomedical Sciences |
College | College of Medicine and Veterinary Medicine |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | Genomics and Proteomics 2 aims to provide students with an overview of the fundamental technological concepts of genomics, functional genomics and proteomics methods using real-world approaches as examples. The course will lay a strong technical foundation on genomics and proteomics, with particular emphasis on experimental design, data handling and data processing. Those skills will be taught with a view how these omics approaches are advancing biomedical research. This is intended to give students a broad idea of the 'omics' field and what it entails, with an opportunity to go into more depth in future years. |
| Course description |
Genomics and Proteomics 2 aims to give students foundational skills in omics data analysis, as well as a broad overview on genomics and proteomics technologies and show how these are applied to real-life biomedical problems.
You will learn about genomics and proteomics methods, the data these experiments produce, as well as about sequence and proteome analysis.
Using existing data in practical classes and assignment will allow you to practice and reinforce your computational skills and how to use them to address questions in biomedical field. You will also improve your academic skills, including planning and documenting your work, literature research, completing a group project, presenting, giving and receiving feedback and reflective practice.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2022/23, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 14,
Seminar/Tutorial Hours 14,
Supervised Practical/Workshop/Studio Hours 56,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
112 )
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| Assessment (Further Info) |
Written Exam
30 %,
Coursework
70 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Exam: 30% total course mark«br /»
Coursework: 70% total course mark, including: practical work assessment portfolio (40%), data analysis project and presentation (30%)«br /»
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| Feedback |
Students will receive summative feedback on their written summary and group presentation.
Both in-course assessments will be preceded by specific formative feedback: Students will receive feedback on their draft analysis report containing an introduction and a proposed data analysis plan and will be given a chance to change their practice.
For the group presentation, groups will have a meeting with a faculty member several weeks before the assignment is due to present their preliminary ideas and receive formative feedback. This will help correct misconceptions, and also gives groups an intermediate milestone in their project timeline.
Additional formative feedback will be given throughout the course, especially in practical and tutorial sessions, so students can check their understanding as they progress. This includes opportunities for formative peer feedback. Students are also encouraged to add a reflective element to their practical write-ups.
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| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Explain basic concepts of next generation sequencing and proteomics and the main differences between the currently used instruments;
- Develop technical skills for analysis and interpretation of 'omics' data, including commonly used online and R based analysis tools, making these skills an integral part of their professional practice;
- Know about available online data repositories and other 'omics' resources;
- Develop an appreciation of the importance of experimental design for genomics and proteomics projects;
- Apply their computational skills to real-life biomedical data, and plan and execute a biomedical 'omics' project
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Reading List
| Biomedical informatics and Functional Genomics. Jonathan Pevsner. Wiley-Blackwell |
Additional Information
| Graduate Attributes and Skills |
This course follows the core areas of technological knowledge for Biomedical Informatics, as identified by the American Medical Informatics Association (Kulikowski et al., J Am Med Inform Assoc 19, 2012): Information documentation, storage, and retrieval.
In addition, the course develops the following core graduate skills and attributes for graduates in Bioinformatics, as identified by Welch et al. (2014) PLoS Comp Biol 10(3).
Computing:
ability to use scientific and statistical analysis software packages, open source software repositories.
Bioinformatics:
analysis of biological data; retrieving and manipulating data from public repositories; ability to manage, interpret, and analyze large data sets; broad knowledge of bioinformatics analysis methodologies; familiarity with functional genetic and genomic data; expertise in common bioinformatics software packages, tools, and algorithms.
Statistics and Mathematics:
application of statistics in the contexts of molecular biology and genomics, mastery of relevant statistical methods (including experimental design, descriptive and inferential statistics, analysis of next generation sequencing data using R)
Biology:
regulatory genomics, systems biology, next generation sequencing, proteomics/mass spectrometry
General:
time management, project management, independence, ability to synthesize information, ability to complete projects, critical thinking, ability to communicate scientific concepts, analytical reasoning, scientific creativity, collaborative ability
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| Keywords | Biomedical informatics,Genomics,Proteomics |
Contacts
| Course organiser | Dr John Menzies
Tel: (0131 6)51 1711
Email: John.Menzies@ed.ac.uk |
Course secretary | Miss Natasha Goldie
Tel:
Email: natasha.goldie@ed.ac.uk |
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