SYSTEMS BIOLOGY - 2020/1
Module code: BMS3072
In light of the Covid-19 pandemic, and in a departure from previous academic years and previously published information, the University has had to change the delivery (and in some cases the content) of its programmes, together with certain University services and facilities for the academic year 2020/21.
These changes include the implementation of a hybrid teaching approach during 2020/21. Detailed information on all changes is available at: https://www.surrey.ac.uk/coronavirus/course-changes. This webpage sets out information relating to general University changes, and will also direct you to consider additional specific information relating to your chosen programme.
Prior to registering online, you must read this general information and all relevant additional programme specific information. By completing online registration, you acknowledge that you have read such content, and accept all such changes.
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.
School of Biosciences and Medicine
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
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.
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.
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.
- 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.
- Quantitative physiology.
- 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 type||Unit of assessment||Weighting|
|Oral exam or presentation||Poster or Oral presentation of a Critical Analysis of a Systems Biology article||30|
|Coursework||RESEARCH GRANT PROPOSAL : DESIGN A NOVEL SYSTEMS BIOLOGY RESEARCH PROJECT||70|
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
- 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.
|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|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Overall student workload
Independent Study Hours: 80
Lecture Hours: 19
Seminar Hours: 13
Practical/Performance Hours: 38
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 for SYSTEMS BIOLOGY : http://aspire.surrey.ac.uk/modules/bms3072
Programmes this module appears in
|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|
|Biochemistry 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|
|Biochemistry MSci (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 2020/1 academic year.