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Module

MMB8052 : Bioinformatics for Biomedical Scientists

  • Offered for Year: 2022/23
  • Module Leader(s): Dr Simon Cockell
  • Lecturer: Professor Joris Veltman, Dr Amir Enshaei, Dr Jamie Soul, Dr Daniel Rico Rodriguez, Dr Louise Reynard, Professor Muzlifah Haniffa, Dr Maria Duenas Fadic
  • Owning School: FMS Graduate School
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 20
ECTS Credits: 10.0

Aims

This module aims to provide a practical introduction to commonly-used informatics technologies for data analysis in the life sciences. Bioinformatics is increasingly integral to the pursuit of molecular biology research. As laboratory methods become more data intensive, a practical knowledge of how this data is handled, processed and analysed is essential to deriving full value from these techniques. This module will principally focus on the application of bioinformatics skills and will provide a grounding in the computational competencies required to work with data generally and modern molecular biology datasets particularly. By the end of the module, students should be able to work with a range of informatics technologies, design and undertake their own analysis of a complex dataset, and use the results of that analysis to synthesize a biological discussion.

Outline Of Syllabus

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

•       Computing for bioinformatics
•       Principles of sequence alignment
•       High Throughput Sequencing (HTS) applications
•       The handling and analysis of HTS data
•       Running bioinformatics analysis at the Linux command line
•       The R statistical programming framework and Bioconductor
•       Statistical analysis of high throughput data using R
•       Data visualisation techniques
•       Practical approaches to pathway analysis
•       Machine Learning and Artificial Intelligence in bioinformatics

In addition, lectures on the module will provide case studies on the outcomes of bioinformatics work in a number of key areas, including genomics, proteomics, transcriptomics and epigenomics.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture101:0010:00Present in person lectures
Guided Independent StudyAssessment preparation and completion120:0020:00Preparation for the practical exercise
Guided Independent StudyAssessment preparation and completion150:0050:00Preparation and submission of practical lab report
Scheduled Learning And Teaching ActivitiesPractical103:0030:00Present in person practicals
Guided Independent StudyDirected research and reading120:0020:00Preparing notes and from lectures and reading
Guided Independent StudySkills practice103:0030:00Consolidation of practical skills
Guided Independent StudyIndependent study140:0040:00Reflective Learning and Reading
Total200:00
Teaching Rationale And Relationship

The core of the module is the practical sessions – these will introduce students to the core tools central to modern bioinformatics, and will demonstrate their use with a variety of modern biological data sets. The practicals will build on each other into a coherent body of knowledge enabling students to apply a range of tools to a complex dataset. Peer support will be encouraged through short group exercises within the practical framework.

The lectures are intended to supplement this material by demonstrating to students the end-products of this computational process – therefore the lectures will be case studies from researchers who make significant use of bioinformatics in their research and will show students how the practical techniques they are learning are actually used in the research process.

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Computer assessment1M25Practical exercise to computationally determine answers to short answer questions
Practical/lab report1M75Practical lab report, particularly focussing on methods and data visualisation. Max 2000 words.
Formative Assessments
Description Semester When Set Comment
Computer assessment1MUnassessed quiz to test understanding of methodologies introduced in practicals.
Assessment Rationale And Relationship

The module is practical-led, and the assessment outcomes are rooted in the application of this practical knowledge. The Short Answer Test summative assessment tests the ability of the students to directly apply the practical techniques being demonstrated through the taught sessions. A series of short questions will be posed, and the answers should be derived automatically by computation. The resulting script which produces the answers is the subject of the assessment, rather than just the answers themselves.
The final assessment is a write-up of the final practical exercise, which will assess the students’ ability to design an analysis approach, apply the appropriate tools and interpret the outputs.

The formative assessment provides students to test their understanding of methodologies introduced in practicals.

Reading Lists

Timetable