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2019/20 Taught Postgraduate Module Catalogue

BIOL5172M Practical Bioinformatics

10 creditsClass Size: 60

Module manager: Dr Sergei Krivov
Email: s.krivov@leeds.ac.uk

Taught: Semester 1 View Timetable

Year running 2019/20

Pre-requisite qualifications

Undergraduate degree in biological sciences

Module replaces

BIOL5255M

This module is not approved as an Elective

Objectives

- To train students in the use of a range of bioinformatics tools
- To provide an overview of the practical problems that bioinformatic tools can be used to solve in academic and industrial biological research
- To work on a defined research problem as part of a team and to describe the investigation and results in written and verbal form

Learning outcomes
On completion of this module, students should be able to:
- describe the types of practical problems to which bioinformatics tools can be applied to;
- use the most important primary and secondary bioinformatics databases and software;
- understand how bio-molecular sequences and structures evolve, the notion of protein families and the principles and problems of phylogenetic tree construction;
- understand the problem of sequence alignment and dynamic programming alignment algorithms;
- use databases associated with bio-molecular structures and tools for structural analysis and visualisation; structure alignment and classification;
- understand the principles of protein secondary structure prediction, comparative modelling, fold recognition and ab initio protein folding algorithms;
- understand the relationship between microscopic dynamics and macroscopic properties of proteins and the relationship between sequence, structure and dynamics in proteins;
- apply the information to solve a defined research problem.

Skills outcomes
The problem based learning aspect of assessment 1 requires:
- teamwork;
- communication with the team;
- creative problem solving; and
- critical thinking.

There is also a peer assessment aspect that requires self awareness.


Syllabus

An overview of the practical problems that bioinformatics tools can be applied to investigate; bioinformatics databases, software and web-based tools; molecular evolution; sequence alignment; dynamic programming and substitution matrices; sequence database searching, methods and statistics; multiple sequence alignment, protein domain families, profiles, patterns and hidden Markov models; iterative searching and PSI-BLAST; phylogenetic tree estimation; protein structure analysis; structural alignment and classification; protein structure prediction, secondary structure prediction, comparative modelling, fold recognition, ab initio; whole genome databases and analyses; gene prediction.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Work-based mentoring23.006.00
Lecture141.0014.00
Practical33.009.00
Private study hours71.00
Total Contact hours29.00
Total hours (100hr per 10 credits)100.00

Private study

2 hours reading per lecture: 28hrs
3 hours preparation for workshops/practicals: 15hrs
Preparation for coursework: 28hrs

Opportunities for Formative Feedback

Progress will be monitored in the practical classes and problem-based learning sessions.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
Group DiscussionProblem-based learning group work30.00
Source AnalysisAnalyse a mystery protein and interpret and evaluate the results in the form of Scientific journal paper (the mystery sequence is given to the students)70.00
Total percentage (Assessment Coursework)100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 30/04/2019

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