BI2BCB2: Bioinformatics and Computational Biology

Module code: BI2BCB2

Module provider: School of Biological Sciences

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 2

Module convenor: Professor Liam McGuffin, email: l.j.mcguffin@reading.ac.uk

Module co-convenor: Dr Andrew Meade, email: a.meade@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: Yes

Last updated: 21 May 2024

Overview

Module aims and purpose

Bioinformatics is an essential part of modern biology. This module will provide you with an introduction to the key concepts of bioinformatics and computational biology. The knowledge and core bioinformatics techniques that are taught will help to equip you with vital programming and computational skills that are required for successful careers in many fields of modern biology. Starting from the fundamentals, it will also cover the basics of algorithms including machine learning, such as Artificial Neural Networks and Genetic Algorithms, and agent-based systems that allow the exploitation of the power of computer intelligence in a bioinformatics context. The module will use practical examples to demonstrate the power of bioinformatics for enhancing research across the biological sciences at all levels; from ecology and zoology to biochemistry, biomedical sciences and pharmacy. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Identify the types of algorithms and intelligent systems used in bioinformatics and computational biology and evaluate how they can be applied to real-world biological problems. 
2. 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. 
3. Design simple algorithms using Python to investigate a biological problem. 
4. Describe the structure of simple programs, the algorithms they encode and predict their output.

Module content

Lectures will cover the theory and real-world application of bioinformatics to research in all fields of biological sciences including 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 mathematical models. 

Lectures will also cover algorithmic topics, such as Artificial Neural Network architectures, and algorithms inspired by natural evolution such as Genetic Algorithms and Evolutionary Programming. 

Students will be taught programming such as an introduction to the Python programming language; variables, constants and strings, control structures, file input/output; lists subroutines and debugging. 

Practical sessions will involve programming and the application of web apps and use of online databases. 

Structure

Teaching and learning methods

The learning outcomes will be met through a mixture of lectures, practical classes/workshops (to apply programming methods using biologically relevant examples), self-directed learning and directed independent study. Appropriate supplementary information and reading lists will be provided on Blackboard. 

Study hours

At least 30 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

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

Assessments with numerical marks

• 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 three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/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.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

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

Reassessment

Additional costs