Module code: BMS3072

Module Overview

Systems biology is widely accepted as a major future direction of biological research. The ethos of systems biology is to generate, analyse and integrate multiple data sets for understanding and modelling a biological system. We want to know the components (molecules) of the system, how they work/interact, and, ideally, have some quantitation: the abundance of a particular component and/or the rates of action/interaction; due to technological advances within molecular biology we are now able to obtain quantitative information about molecules within a biological system on a large-scale.

The purpose of this module is to introduce students to the basic concepts of systems biology. The module includes work relevant to prokaryotic and eukaryotic systems and is thus suitable for all bioscience students. Learning methods include: Lectures, computational practical sessions, seminars, readings, workshops and research and problem solving during computer based investigations.

Module provider

School of Biosciences and Medicine

Module Leader

BARBERIS Matteo (Biosc & Med)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

Module cap (Maximum number of students): N/A

Overall student workload

Independent Learning Hours: 80

Lecture Hours: 19

Seminar Hours: 13

Practical/Performance Hours: 38

Module Availability

Semester 2

Prerequisites / Co-requisites

BMS2036 Methods in Molecular Biology and Genetics This module has a capped number and may not be available to ERASMUS and other international exchange students. Please check with the Global Engagement Office exchange and study abroad team.

Module content

Indicative content includes:

Founding ‘good research practice’ concepts

  • An introduction to Systems biology

  • How to design a systems biology experiment.

  • How to [critically] read a paper

  • Research proposal “surgery” sessions where students can discuss their proposal with peers and academics.

Bioinformatics analysis

Databases, tools and statistical analysis supporting high-throughput data comprising:

  • Genomics : Sequence analysis

  • Metagenomics and metatranscriptomics: Application of high-throughput sequencing to investigate microbial communities.

  • Transcriptomics: Microarrays and RNA-seq: Which genes are expressed? Functional analysis of genes.

  • Phenomics & Proteomics : Identifying substrate utilisation, proteins in the system

Section will include a research seminar discussing current bioinformatics research and applications in systems biology.

Mathematical modelling

  • Founding concepts in mathematical modelling

  • Conducting simulations of cellular processes using dedicated software

  • Metabolic modelling and Flux Balance Analysis

Section will begin with a research seminar discussing current mathematical modelling research and applications in systems biology.

Metabolic modelling

  • Quantitative physiology.

  • Bioenergetics.

  • Metabolic control analysis : Determination of control coefficients. Control in linear and branched pathways.

  • Modelling genome scale metabolic networks.

  • Section will begin with a research seminar discussing current metabolic modelling research and applications in systems biology.

Assessment pattern

Assessment type Unit of assessment Weighting
Oral exam or presentation Poster or Oral presentation of a Critical Analysis of a Systems Biology article 30

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate

  • An ability to understand and accurately report the outputs of bioinformatics analysis and mathematical and metabolic models.

  • An ability to select the most appropriate methods for answering their own independent research question(s).

  • An awareness of cutting-edge research in Systems Biology.

Group discussions between students, and lead by academics in seminar sessions, will further demonstrate breath of the field and its role in contemporary life sciences.

The grant proposal assessment is key to providing students with the opportunity of demonstrating their ability to formulate independent research ideas involving application of systems biology approaches.

Thus, the summative assessment for this module consists of:

  • A poster or oral presentation of the critical analysis of a recent scientific article involving the application and analysis of a systems biology approach to results combining Bioinformatics, -omics analysis, and mathematical and metabolic modelling. The analysis will demonstrate the understanding of the advantages and limitations of those approaches, and how they can be used to understand cellular phenomena. Depending on the number of students enrolled for the module, it is expected that each article will be shared by groups of 2 students. Reports to be submitted two weeks before the end of the module.

  • Presentation of student’s original idea as a grant proposal (submitted at the end of the module).

Formative assessment and feedback

The students will receive formative feedback from their peers and academics during the seminars. The feedback given here will directly support the development of a research proposal. We provide extensive feedback on research grant proposals during the scheduled proposal workshop sessions, before submission

Module aims

  • To introduce the field of Systems Biology and the key topics within it
  • To increase awareness of the information that can be gained from the application of high-throughput technologies ("-omics" : genomics, phenomics, proteomics, transcriptomics, metabolomics, metagenomics and metatranscriptomics) employed to measure parameters at a systems level, and how this data can be exploited using bioinformatic and/or modelling techniques.
  • To provide practical understanding of computer simulations of living systems, computational analysis of experimental data and how to interpret the results.
  • To increase awareness of current research within the field of systems biology.

Learning outcomes

Attributes Developed
001 Understand the basic quantitative techniques used within the field of Systems Biology KPT
002 Analyse high-throughput data sets using current available softwares/web-tools CP
003 Use key bioinformatic tools for interpreting your results. CPT
004 Use software tools for computer simulations of molecular interaction networks. CPT
005 Integrate diverse data sets to understand organisms at a systems level CPT
006 Present your ideas in a concise and cohesive style of a research grant proposal CPT
007 Present your ideas in an oral presentation PT
008 Design an experiment KCPT
009 Critically review the literature KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Give students understanding and awareness of systems biology approaches to enable independent and creative application of these approaches to answer research hypotheses and global challenges. We will provide basic skills of computational data analysis and mathematical modelling. Assessment is focussed on critical knowledge evaluation and ability to formulate independent research ideas.

The learning and teaching methods include:

  • Lectures, including online lectures (1 hour each week)

  • Research seminars (4 hours)

  • Research proposal “surgery” workshop (Entire day)

  • Computer practicals (online; supported using online resources and in-class support seminars, 4 hours each week)

  • Seminars on designing experiments and critical review (3 hours)

  • Presentation of original ideas in the form of grant proposal: 60 hours

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list
Upon accessing the reading list, please search for the module using the module code: BMS3072

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Biomedicine with Data Science BSc (Hons) 2 Compulsory A weighted aggregate mark of 40% is required to pass the module
Biomedicine with Electronic Engineering BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Microbiology (Medical) BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Biotechnology BSc (Hons) 2 Compulsory A weighted aggregate mark of 40% is required to pass the module
Microbiology BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Biomedical Science BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Biological Sciences BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2019/0 academic year.