2024/25 Taught Postgraduate Module Catalogue

OGDS5100M High-Throughput Technologies

15 creditsClass Size: 150

Module manager: David Westhead
Email: d.r.westhead@leeds.ac.uk

Taught: 1 Jan to 28 Feb, 1 Jan to 28 Feb (adv year), 1 Jul to 31 Aug View Timetable

Year running 2024/25

Pre-requisite qualifications

Students are required to meet the programme entry requirements prior to studying the module.

Module replaces

None

This module is not approved as an Elective

Module summary

The module aims to provide an understanding of the use of high-throughput biomolecular data generation methods. The emphasis will be on understanding methods and the data that they typically give. Techniques covered will include whole genome/exome sequencing, gene expression, RNA-seq and epigenetics, proteomics, chemical proteomics, high-throughput RNA biology, single-cell methods and metabolomics. Data analysis methods will be discussed but there will not be a strong emphasis on statistical methods that are covered in other modules.

Objectives

The objectives of the module are to:

- Introduce students to a range of high-throughput experimental methods currently being used in biochemistry, molecular biology and genetics;
- Make students aware of data analysis methods and issues associated with the interpretation of high-throughput data;
- Allow students to appreciate the applications of high-throughput data generation to advance bioscience and medicine.

Learning outcomes
On successful completion of the module students will be able to:

1. Describe of a range of currently important experimental methods which generate high-throughput data in molecular biology and genetics;
2. Explain how these high-throughput methods work;
3. Demonstrate an understanding of the specific and generic data analysis methods and issues associated with high throughput data;
4. Describe how high-throughput data can advance bioscience and medicine;

Syllabus

Indicative content for this module includes:

1. Introduction to DNA sequencing
2. Introduction to RNA sequencing and Epigenomics
3. Proteomics
4. Translatomics
5. Single Cell Methods
6. Proteomics

Teaching methods

Delivery type	Number	Length hours	Student hours
Discussion forum	6	2.00	12.00
WEBINAR	1	1.50	1.50
WEBINAR	5	1.00	5.00
Independent online learning hours			42.00
Private study hours			89.50
Total Contact hours			18.50
Total hours (100hr per 10 credits)			150.00

Private study

Across each week of learning students will actively engage with pre-prepared teaching and learning resources which scaffold learners to achieve learning outcomes (independent online learning). Each week follows a set pattern of acquiring knowledge which is then applied to a substantive activity which will usually be authentic to real-world application. Weekly asynchronous discussions (such as discussion boards) allow for peer-to-peer and peer-to-tutor discussion which supports completion of the substantive activity. At the end of each week of learning students consolidate their learning through reflective activities and a weekly live webinar session with the module tutor. Each unit also provides students with the opportunity for exploration and self-directed learning as is expected at masters level (private study).

Opportunities for Formative Feedback

The module’s digital learning materials provide regular opportunities for participants to check their understanding and gain feedback (e.g., case studies with short answer questions and automated feedback, MCQs with detailed feedback on correct/incorrect answers). 

The individual unit webinars and discussion forums provide opportunities for formative feedback from peers and tutors.  

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Essay	2,000 words	70.00
Reflective log	1,000 words	30.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 18/11/2024

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