BI2BT5-Introduction to Bioinformatics & Computational Biology

Module Provider: School of Biological Sciences
Number of credits: 10 [5 ECTS credits]
Level:5
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3

Module Convenor: Prof Liam McGuffin
Email: l.j.mcguffin@reading.ac.uk

Type of module:

Summary module description:

Bioinformatics is an essential part of modern biology. This module will provide students with introduction to the key concepts of bioinformatics and computational biology and it is aimed at second or third year students. The knowledge and core bioinformatics techniquesÌýthat areÌýtaught will help to equip students with the vital computational and programming skills that are required for successful careers in many fields of modern biology. The module does not have any prerequisites and it will use practical examples to demonstrate the power of bioinformatics for enhancing research across the biological sciences at all levels; from molecular and cellular biology to zoology and ecology.

Aims:
The aim of this module is to provide an introduction to the key concepts of bioinformatics and computational biology for second or third year students, which will equip them with core bioinformatics skills required for successful careers in many fields of modern biology. The module will not have any prerequisites and will use practical examples to demonstrate the power of bioinformatics for enhancing research across the biological sciences; from ecology and zoology to biochemistry, biomedical sciences and pharmacy.

Assessable learning outcomes:

Students will be able to:

• Evaluate when and where computational methods should be used in biology and know how they can be applied to make predictions, formulate new hypotheses and suggest new experiments


• Compare, contrast and evaluate the current publicly available bioinformatics tools, web apps and databases and deploy them to make useful predictions about sequences with unknown structures and functions


• Understand the structure of simple Python programs, describe the algorithms they encode and predict the output


• Identify and fix bugs in simple Python programs


• Construct a simple Python program which incorporates the following concepts: file I/O, control structures, regular expressions, hashes/arrays


• Compare sequences and use/develop simple programs to visualise evolutionary relationships between organisms (e.g. using phylogenetic trees)


• Develop and code simple algorithms using Python to investigate a biological problem

Additional outcomes:

This module offers a range of additional outcomes, including:

1. The enhancement of teaching and research synergies, (one of ºÚ¹Ï³ÔÁÏÍø’s learning and teaching enhancement priories)


2. The enhancement of graduate employabilty - it is a cutting edge topic and the transferable skills are highly sort after by industry


3. The enhancement of performance in final year projects - the skills learned will complement final year projects offering an alternative to traditional lab based research, this module will increase the appeal of non-lab based projects to a wider range of students.

Outline content:
10 lectures on the theory and real world application of bioinformatics to research in all fields of biological sciences covering topics such as: the history of bioinformatics and the growth in biological data; sequence alignment methods and tools; servers, databases and web apps; computational biology in ecology; methods for predicting structure, functions and interactions of proteins (and nucleic acids) from sequences; using computational methods to understand evolution; £omics technologies, data management and predictive tools; simulations in computational biology; use of molecular dynamics simulations; use of mathematical models.

10 programming lectures covering topics such as: an introduction to the Python programming language; variables, constants and strings, control structures, file input/output; lists/hashes/associative arrays; regular expressions; subroutines and debugging.

10 practical sessions on programming and the application of web apps and online databases.

Brief description of teaching and learning methods:
Computational biology will be a 10 credit module, with 35-40 contact hours. 10 hours will be used to introduce the theory, application and methods used in computational biology. 10 hours will be used to introduce programming topics, followed by 10 one or two hour practical classes applying the programming methods using biologically relevant examples.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures		20
Practicals classes and workshops		20
Guided independent study:		60
Ìý	Ìý	Ìý	Ìý
Total hours by term		100
Ìý	Ìý	Ìý	Ìý
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Report	40
Project output other than dissertation	50
Set exercise	10

Summative assessment- Examinations:
No examination

Summative assessment- Coursework and in-class tests:
Report (extended essay) - 40%
Project (programming) - 50%
Open book quizzes on Blackboard to accompany practical sessions in PC labs and to be completed within the week - 10% (1% per practical session)

Formative assessment methods:
Formative assessments will include interactive quiz questions and/or discussions to be held at regular intervals during the lectures, which will help reinforce and recap on the key points raised. The quizzes and discussions will help to improve student attainment, as well as being used to monitor the group progress and understanding of the module material.

Penalties for late submission:

The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:
A mark of 40% overall.

Reassessment arrangements:
By examination, August/September.

Additional Costs (specified where applicable):

1) Required text books:Ìý None

2) Specialist equipment or materials:Ìý None

3) Specialist clothing, footwear or headgear:Ìý None

4) Printing and binding:Ìý None

5) Computers and devices with a particular specification:Ìý None

6) Travel, accommodation and subsistence:Ìý None

Last updated: 22 September 2022