2018/19 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 (Sep to Jan) View Timetable
Year running 2018/19
Pre-requisite qualifications
Undergraduate degree in biological sciencesModule replaces
BIOL5255MThis 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 type | Number | Length hours | Student hours |
Work-based mentoring | 2 | 3.00 | 6.00 |
Lecture | 14 | 1.00 | 14.00 |
Practical | 3 | 3.00 | 9.00 |
Private study hours | 71.00 | ||
Total Contact hours | 29.00 | ||
Total hours (100hr per 10 credits) | 100.00 |
Private study
2 hours reading per lecture: 28hrs3 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 type | Notes | % of formal assessment |
Group Discussion | Problem-based learning group work | 30.00 |
Source Analysis | Analyse 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 websiteLast updated: 18/04/2018
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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