GENE30070 Undergraduate Research 2

Academic Year 2022/2023

This is a computational research-based module, aimed at students with a strong interest in genomics, genetics, microbiology, computational biology and/or bioinformatics. The module follows on from GENE30060, but ti is not necessary to take both. In GENE30070 students will analyse whole genome sequence data, derived from next generation sequencing of yeasts collected from Irish soil, or obtained from other sources. Some of this data will never have been assembled or analysed previously. Students will use computational methods to assemble and annotate genomes, to identify variations such as Single Nucleotide Polymorphisms, and to propose and address research hypotheses. The approaches used and questions posed will be determined by student input. The module will provide training in state-of-the art technologies in genome analysis. Part of the assessment is to write a short scientific paper describing novel results. In previous years, some of these have been accepted for publication in scientific journals.The module therefore provided an opportunity to engage in novel research. No previous coding experience is required, but it could be advantageous (for example, taking GENE30040 or another introductory programming module). Module teaching will be face-to-face where possible, and online where necessary. Students will need their own laptop/computer (not tablet) for the duration of the module. The module will be examined by continuous assessment, including an in-trimester computer-based exam.

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Curricular information is subject to change

Learning Outcomes:

1. Learn how to use a Unix operating system.
2. Obtain training in bioinformatic analysis of novel biological data
3. Learn how to propose hypotheses based on genome sequencing.
4. Learn how to write a short scientific paper.
5. Opportunity to contribute to a large-scale research project.

Student Effort Hours: 
Student Effort Type Hours
Computer Aided Lab

48

Autonomous Student Learning

60

Total

108

Approaches to Teaching and Learning:
Active/task based learning: bioinformatic exercises. Critical writing: prepare a scientific paper. Lectures. 
Requirements, Exclusions and Recommendations
Learning Recommendations:

Students are encouraged to take GENE30040 Programming for Biologists (or an equivalent module)


Module Requisites and Incompatibles
Not applicable to this module.
 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Class Test: In class assessment based on bioinformatics exercises and lectures. Week 8 n/a Graded No

50

Assignment: Genome assembly and annotation, plus writing scientific paper. Week 11 n/a Graded No

50


Carry forward of passed components
Yes
 
Remediation Type Remediation Timing
In-Module Resit Prior to relevant Programme Exam Board
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Feedback will be provided following the in class test, and during all tutorial sessions.

Name Role
Dr Kevin Byrne Lecturer / Co-Lecturer
Professor Kenneth Wolfe Lecturer / Co-Lecturer
Assoc Professor Peadar Ó Gaora Lecturer / Co-Lecturer