Full Title:Bioinformatics
Language of Instruction:English
Module Code:AGRIS9Z03
Credits: 7.5
Valid From:Semester 1 - 2019/20 ( June 2019 )
Module Delivered in 2 programme(s)
Module Description: This module aims to provide students with knowledge and competence in the use of computational biology in the analysis of molecular data. This course has emphasis on bioinformatics related to High-Throughput Sequencing (HTS) processing, analysis and interpretation of output of genomics data using bioinformatical tools.
Learning Outcomes:
On successful completion of this module the learner should be able to
  1. Discuss the omics technologies and the impacts of bioinformatics in the agricultural sector
  2. Demonstrate a mastery of advanced theoretical knowledge and skills relating to high-throughput sequencing applications
  3. Critically assess, interpret and manipulate raw sequencing data
  4. Evaluate the impact of high-throughput sequencing in the agricultural sector

Module Content & Assessment

Indicative Content
Bioinformatics and its Applications
High-Throughput Sequencing workflow, denovo genome assembly and annotation, transcriptomics using RNA-seq, 16S metagenomics, epigenomics
Bioinformatics Workstation
Working on a Unix system, filesystem basics, commands for working with directories and files, issuing commands on a Unix system, viewing and editing files
Tools for Bioinformatics
Sequence analysis, pairwise alignment and database searching
Using search engines, NCBI, BLAST, Ensembl, UniprotKB, Pfam, Global and local pairwise alignment, pairwise sequencing comparison using specialised software (e.g. splign), prediction of protein structure and function, multiple sequence alignment
High-Throughput Sequencing
Genome assembly, interpretation and quality check of raw sequencing data, align HTS data against a reference genome, annotating and analysing whole genome sequencing
Practical Exercises
Practicals will be delivered through computer based sessions. Computer-based practicals will allow the Student to become familiar with different types of genetic data sets and the use of various open source software for sequence/genome analyses. By completing these practicals, students will strengthen their understanding of basic bioinformatics applications in an agricultural context.
Learning and Teaching Resources
Students will receive feedback in the following ways:
- Discussions with the lecturer will provide feedback throughout the module - Academic feedback will be provided on continuous assessment - Feedback on final examination will be given in line with the Institute’s policy
Students will be supported in their learning in the following ways:
- Formal lectures - IT based tutorials - Small group investigation - MOODLE site with tutor directed materials (e.g. links to literature, e-learning materials and contemporary scientific related topics) - Independent study
Assessment Breakdown%

Full Time

No Course Work
Assessment Type Assessment Description Outcome addressed % of total Marks Out Of Pass Marks Assessment Date Duration
Project Students will conduct research in a current omics related project. During this project, students will analyse and evaluate the used of omics technologies relating to the agricultural sector. 1,2,4 60.00 0 0 n/a 0
Assessment Type Assessment Description Outcome addressed % of total Marks Out Of Pass Marks Assessment Date Duration
Practical/Skills Evaluation Students will participate in weekly computer-based practicals. During practical sessions, students will evaluate and appraise different bioinformatical tools pertinent to sequence/genome analysis. The students will use specialised techniques, skills and modern computer-based tools necessary for genome assembly and annotation. 2,3 40.00 0 0 n/a 0
No End of Module Formal Examination
Reassessment Requirement
A repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

DKIT reserves the right to alter the nature and timings of assessment


Module Workload & Resources

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture No Description 1.00 Every Week 1.00
Practical No Description 2.00 Every Week 2.00
Directed Reading No Description 3.00 Every Week 3.00
Independent Study No Description 5.00 Every Week 5.00
Online Learning (non contact) No Description 1.00 Every Week 1.00
Total Weekly Learner Workload 12.00
Total Weekly Contact Hours 3.00
This course has no Part Time workload.
Recommended Book Resources
  • Andreas D. Baxevanis, B. F. Francis Ouellette 2004, Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, 3rd Ed., Wiley-Blackwell
  • Shui Qing Ye 2007, Bioinformatics: A Practical Approach, Chapman and Hall/CRC
Recommended Article/Paper Resources
Supplementary Article/Paper Resources
Other Resources

Module Delivered in

Programme Code Programme Semester Delivery
DK_SAGBI_9 Master of Science in Agricultural Biotechnology 1 Mandatory
DK_SAGPD_9 Postgraduate Diploma in Agricultural Biotechnology 1 Mandatory