Skip to main content

Module

CSC3424 : Bioinformatics

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Jaume Bacardit
  • Other Staff: Dr Simon Cockell
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semesters
Semester 2 Credit Value: 10
ECTS Credits: 5.0

Aims

1)       To familiarise students with computational approaches to tackling biological data handling and analysis
2)       To introduce the concepts of algorithm design for molecular biology data
3)       To develop skills in algorithm design with an emphasis on solving biological problems
4)       To understand the most appropriate type of algorithms for differing analytical problems in molecular biology and to introduce some of the most appropriate implementation strategies.

Outline Of Syllabus

•       Molecular and cell biology
•       Genetic Material and Genomes
•       Gene expression, transcriptomics and proteomes
•       Sequencing technologies & algorithms
•       Genome Annotation
•       Evolution
•       Sequence comparison and alignment
•       Basic phylogenetics
•       Basic transcriptomics & proteomics
•       Protein structure prediction
•       Introduction to ontology & data standards
•       Biological network analysis

Teaching Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture90:304:30Synchronous online sessions, one per week to ask questions on the lectures
Guided Independent StudyAssessment preparation and completion121:0012:00Lecture follow-up
Guided Independent StudyAssessment preparation and completion110:0010:00Coursework 1
Scheduled Learning And Teaching ActivitiesLecture300:3015:00Material for lectures, split in 30’ sessions, non-synchronous online
Scheduled Learning And Teaching ActivitiesPractical81:008:00Practicals, non-synchronous online
Scheduled Learning And Teaching ActivitiesPractical60:454:30Synchronous online sessions to ask questions on the practicals&coursework, 2sessions in 3 blocks
Guided Independent StudyIndependent study161:0016:00Background reading
Guided Independent StudyIndependent study130:0030:00Coursework 2
Total100:00
Teaching Rationale And Relationship

Lectures will be used to introduce the basic material and the more advanced theoretical topics.
Practical sessions, mostly computer based, will give the student opportunity to build up skills in algorithm design development and implementation.

Assessment Methods

Please note that module leaders are reviewing the module teaching and assessment methods for Semester 2 modules, in light of the Covid-19 restrictions. There may also be a few further changes to Semester 1 modules. Final information will be available by the end of August 2020 in for Semester 1 modules and the end of October 2020 for Semester 2 modules.

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report2M100A practical report in which the bioinformatics algorithms covered in the module are put to practice - 2500 words
Formative Assessments
Description Semester When Set Comment
Practical/lab report2MShort document explaining the design of a bioinformatics analysis, tied to ‘practical report 2’ – 500 words
Assessment Rationale And Relationship

The coursework-based assessment will test skills both the understanding of the students on the covered topics as well as their practical skills in algorithm design and solving real world problems.

Reading Lists

Timetable