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Curricular information is subject to change
On completion of this module students should be able to identify and apply some of the standard methods in computational analysis of biosequences. They should understand why sequence regions are typically conserved or variable in populations and in evolution, and how that information may be applied. They should understand some of the challenges and solutions involved in dealing with large biological datasets, such as the problem of multiple testing across many molecular variants.Indicative Module Content:
Protein and DNA sequence databases.
Trees based on similarities of sequences.
Analysing genome wide variation in genes.
Somatic mutation databases in cancer.
|Student Effort Type||Hours|
|Autonomous Student Learning||
It is recommended that students taking this module will have successfully completed either BMOL20010 or GENE20010, or other modules with equivalent learning outcomes in molecular biology.
|Description||Timing||Component Scale||% of Final Grade|
|Assignment: Project write up for an assigned protein/gene analysis. There will be opportunities for a component of the work to be completed as a group.||Coursework (End of Trimester)||n/a||Graded||No||
|Class Test: The class tests will assess understanding of concepts and of particular data analyses mainly via MCQ.||Throughout the Trimester||n/a||Graded||No||
|Resit In||Terminal Exam|
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
You will complete different tasks each week which will accumulate into your week 11 presented group slideshow (groups of three). You will get some feedback on your learning from completing online MCQs (ungraded). You will get feedback after presenting the group project which will give insights into your final individual write-up. you will get a final piece of short feedback on your individual submission after it is graded.
|Professor Desmond Higgins||Lecturer / Co-Lecturer|
|Professor Kenneth Wolfe||Lecturer / Co-Lecturer|
|Assoc Professor Peadar Ó Gaora||Lecturer / Co-Lecturer|
|Mr Sean Bergin||Tutor|
|Mr Donagh Egan||Tutor|
|Ms Olateju Idowu||Tutor|
|Gillian Mc Hugo||Tutor|
|Miss Stephanie Mc Kenna||Tutor|
|Mr Eoin O Cinneide||Tutor|
|Mr Adam Ryan||Tutor|
|Mr Patrick Timmons||Tutor|
|Marina Villacampa Fernandez||Tutor|
|Lecture||Offering 1||Week(s) - 1, 2||Mon 16:00 - 16:50|
|Lecture||Offering 1||Week(s) - 3, 4||Mon 17:00 - 17:50|
|Tutorial||Offering 1||Week(s) - 5, 8, 9, 10, 11, 12||Mon 16:00 - 16:50|
|Tutorial||Offering 2||Week(s) - 5, 7, 9, 10, 11, 12||Thurs 10:00 - 10:50|
|Tutorial||Offering 3||Week(s) - 5, 7, 9, 10, 11, 12||Thurs 11:00 - 11:50|
|Computer Aided Lab||Offering 1||Week(s) - 12||Tues 15:00 - 16:50|
|Computer Aided Lab||Offering 1||Week(s) - 2, 3, 7, 8, 9, 10, 11||Tues 15:00 - 16:50|
|Computer Aided Lab||Offering 1||Week(s) - 4, 5||Tues 15:00 - 16:50|
|Computer Aided Lab||Offering 2||Week(s) - 2, 3, 4, 5, 7, 8, 9, 10, 11, 12||Thurs 16:00 - 17:50|
|Computer Aided Lab||Offering 3||Week(s) - 2, 3, 4, 5, 7, 8, 9, 10, 11, 12||Fri 14:00 - 15:50|