Surrey University Stag


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 together, 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 both small and large scales.

The purpose of this module is to introduce students to the basic concepts of Systems Biology. The module includes subjects relevant to prokaryotic and eukaryotic systems and is thus suitable for all bioscience students. Learning methods include: lectures, seminars, computational practical sessions, article discussion, workshops and research and problem solving during both lectures and 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

JACs code: C910

Module cap (Maximum number of students): 52

Overall student workload

Workshop Hours: 16

Independent Learning Hours: 58

Lecture Hours: 22

Seminar Hours: 5

Tutorial Hours: 3

Practical/Performance Hours: 16

Captured Content: 30

Module Availability

Semester 2

Prerequisites / Co-requisites


Module content

Indicative content includes:

Founding ‘good research practice’ concepts

  • An introduction to, and concepts of Systems Biology

  • How to design a Systems Biology experiment

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

Mathematical Modelling

  • Founding concepts in mathematical modelling of dynamic systems

  • Building mathematical models and analysis of model parameters

  • Conducting simulations of cellular processes using specialised software

  • Computer practicals where software for modelling analyses will be presented

  • Research seminar will discuss examples of mathematical modelling in scientific research

Modelling complex biological systems

  • Building a biological network

  • Integrating mathematical modelling with experimental data

  • Modelling cell cycle control: experimental background and model building

  • In silico model predictions and experimental validation

  • Modelling genome scale metabolic networks

  • Flux Balance Analysis: stoichiometric coefficients and stoichiometric matrix

  • Fluxes, biomass and optimization criteria

  • Research seminars where mathematical modelling research and applications in Systems Biology will be presented and discussed

Bioinformatic analyses

  • Concepts of –omics and network biology in understanding human health and disease

  • –omics data (genomics, transcriptomics, proteomics, interactomics, metabolomics, meta–omics): data generation, processing and analysis

  • Sequence analysis, statistical analysis and biological interpretation

  • Molecular interaction networks: reconstruction from data/computational approaches and basic concepts of network analysis

  • Data integration – why one ‘–ome’ is not enough and approaches to data integration

  • Research seminars where Bioinformatics research and applications in Systems Biology will be presented and discussed

Assessment pattern

Assessment type Unit of assessment Weighting

Alternative Assessment


Assessment Strategy

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

  • Ability to understand and accurately report the outputs of mathematical and metabolic models and bioinformatic analysis

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

  • Awareness of cutting-edge research in Systems Biology

Discussions between students in a workshop, 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:

  • An oral poster presentation on the critical analysis of a recent scientific article involving the application and analysis of a Systems Biology approach to results combining (any of) Bioinformatics, –omics analysis, and mathematical and metabolic modelling. The analysis will demonstrate the understanding of advantages and limitations of those approaches, and how they can be used to understand and gain further knowledge of 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 workshops. The feedback given here will directly support the development of a research grant proposal. Extensive feedback will be provided on research grant proposals during the scheduled "surgery" workshop session, before submission.

Module aims

  • To introduce the field of Systems Biology and the key topics within it
  • To provide examples of how experimental and computational approaches may be integrated, to address behaviours of complex biological systems
  • 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 the information that can be gained from the application of high-throughput technologies ("-omics": genomics, transcriptomics, proteomics, interactomics, metabolomics, meta-omics) employed to measure parameters at a systems level, and how this data can be exploited using bioinformatic and/or modelling techniques
  • 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 KCPT
007 Present your ideas in an oral poster presentation PT
008 Design a Systems Biology 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 their independent and creative application to answer research hypotheses and global challenges. We will provide basic skills of mathematical modelling and computational data analysis. Assessment is focussed on the critical evaluation of a scientific journal article and the ability to discuss and formulate independent research ideas.

The learning and teaching methods include:

  • Lectures, including online lectures (24 hours)

  • Tutorials on module content and assessments (3 hours)

  • Research seminars on designing experiments (11 hours)

  • Computer practicals (16 hours) plus online resources

  • Journal article critical review workshop (full day)

  • Research proposal “surgery” workshop (full day)

  • Presentation of original Systems Biology ideas in the form of research 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

Other information

This module has a capped number and may not be available to ERASMUS and other international exchange students. Please check with the International Engagement Office email:

Programmes this module appears in

Programme Semester Classification Qualifying conditions
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
Biochemistry BSc (Hons) 2 Optional A weighted aggregate mark of 40% is required to pass the module
Biochemistry MSci (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 2021/2 academic year.