Undergraduate

modules

Modules

BMS3025 : Bioinformatics

Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

Bio-research at universities or in industry requires an understanding of modern data-analysis (bioinformatics and health informatics) tools and this modules aims to introduce students to such tools, and also provide them with an opportunity to use a number of the tools in the analysis of data. Specifically the module aims to:

• reacquaint students with tools they have previous used in CMB2000
• explore the use of health informatics to improve the quality and safety of patient care
• examine the uses of various tools to analyse the large datasets (e.g genomic, proteomic, metagenomics, microbiomic, metabolomic)
• generate an understanding, and an appreciation, of databases, ontologies, workflows, structural prediction, and coding
• give the students the theory behind, and the practice in using, a number of modern bioinformatic analysis tools

Outline Of Syllabus

The following topic and themes will be covered in this module:

• a review of the bioinformatics tools previous used in CMB2000
• the use of health informatics to improve the quality and safety of patient care
• the use of various tools to analyse the large datasets (e.g genomic, proteomic, metagenomics, microbiomic, metabolomic)
• databases structure
• the use of ontologies, workflows, and computer code in data analysis
• protein structure prediction
• theory behind, and practice in using, a number of modern bioinformatic analysis tools

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion120:0020:00Assessment
Scheduled Learning And Teaching ActivitiesLecture101:0010:00N/A
Scheduled Learning And Teaching ActivitiesPractical13:003:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching21:002:00Seminar - First pre-practical second post
Guided Independent StudyIndependent study165:0065:00Private Study
Total100:00
Teaching Rationale And Relationship

Lectures will be used to impart information in a concise manner, to highlight areas of importance and to interrelate with directed reading and self-directed study. The lectures will be used to introduce a range of bioinformatics tools and analysis strategies.
The first seminar will introduce the practical, and the associated assessment, hence it will be held before the practical session. The second seminar will follow the practical to address any concerns and to reinforce the material, and to help the students prepare for the assessment.
The practical will provide the students with a structured session in which they can explore and develop their understanding of the bioinformatics tools introduced in the lectures.
Private study will be used for self-directed learning, including further reading.

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Case study1M100Report on the analysis of large sequence data-set
Formative Assessments
Description Semester When Set Comment
PC Examination1MFormative online assessment (on BB) in the form of post-lecture MCQ
PC Examination1MMCQs embedded within practical so students can assess understanding and progress.
Assessment Rationale And Relationship

Formative Assessment: The students will be provided with a series of formative post-lecture MCQ exercises which they can use to explore their understanding of the material delivered in the lectures and the online training session.

Summative Assessment: In the summative assessment the students will be presented with a large dataset which they have to analyse using the tools, ideas and approaches covered in the lectures and in the online training. The assessment will explore their understanding of the material taught, as well as push their critical thinking and data-analysis skills. Their results will be presented as 1,500 word report, which will have to contain appropriate diagrams, tables and figures.

Reading Lists

Timetable