Gwybodaeth Modiwlau

Module Identifier
CS31810
Module Title
Computational Bioinformatics
Academic Year
2019/2020
Co-ordinator
Semester
Semester 1
Pre-Requisite
CS24420 or CS21120 CC24420 or CC21120, or MA25220, or MT25220
Reading List
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 20 x 1 Hour Lectures
Practical 10 x 1 Hour Practicals
 

Assessment

Assessment Type Assessment length / details Proportion
Semester Assessment Essay with accompanying source code/data  3000 words plus code, data and graphs  100%
Supplementary Assessment Essay with accompanying source code/data  Resubmission of failed assignment  100%

Learning Outcomes

On successful completion of this module students should be able to:

1. Describe the current algorithms and data structures used in bioinformatic sequence analysis.

2. Perform an analysis of a set of DNA sequences and interpret the results.

3. Demonstrate an understanding of the potential sources of error in this type of data and subsequent analyses.

Brief description

This module introduces students to computational bioinformatics. The module will cover the basics of DNA sequence analysis, including sequencing, assembly, similarity/searching, and annotation. The emphasis will be on the computational algorithms that allow us to discover information from biological sequence. This is a fast-moving field, and the content of the course will cover classic algorithms and newer developments.

Aims

Computational Bioinformatics is a subject in demand in industry and in academia. Graduates would be highly employable.

Content

The basics of DNA, RNA and protein sequences.

Sequencing. Short read and long read sequencing.

Sequence quality. Inspecting the results of sequencing. Analysis of the types of error.

Assembly. Reference genomes.

Sequence similarity, alignment and k-mer algorithms.

Burrows Wheeler transformations and short read alignment.

Genome annotation. ORF-finding. Codons, frames, introns/exons, non-coding regions.

Ethics and security when working with genomic data.

Module Skills

Skills Type Skills details
Application of Number Inherent in subject.
Communication Documenting code, essay writing.
Improving own Learning and Performance Automatic feedback from the process of using and coding the computational tools.
Information Technology Inherent in subject.
Personal Development and Career planning No, though the skills acquired during this module are in high demand.
Problem solving Inherent in subject matter.
Research skills Using a computer and online tools. Readings from current scientific literature.
Subject Specific Skills Data analysis skills, algorithm and data structure skills.
Team work Will be used for some workshops/pracs.

Notes

This module is at CQFW Level 6