CSC8313 : Bioinformatics Theory and Practice
- Offered for Year: 2024/25
- Module Leader(s): Dr Katherine James
- Lecturer: Dr Emanuela Torelli
- Owning School: Computing
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 20 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
To introduce the data that arises from studies in molecular biology.
To reinforce the theory underlying the concepts and techniques of sequence analysis and postgenomic bioinformatics.
An understanding of the distributed and available resources for bioinformatics analyses.
This module provides an understanding of the basic theory behind bioinformatics analyses, the computational and algorithmic approaches underpinning modern bioinformatics approaches, and experience in practically applying that theory. The module introduces basic concepts of molecule biology, sequence analysis and genomic era biology. It introduces a number of many different tools and their usage, as well as the analysis algorithms behind some of them including BLAST and dynamic programming. More advanced approaches to biological sequence analysis, assembly, comparison and annotation are also introduced, including comparative genomics. The basics of protein motifs, structure and families, and phylogenetics are introduced. Later parts of the module introduces the concepts behind modern postgenomic bioinformatics including material of biological pathways and networks.
Outline Of Syllabus
Basic concepts of molecular biology: genomes, transcripomes, proteomes.
Database searching tools.
Sequencing algorithms.
Sequence analysis: genome assembly and annotation, sequence alignment and comparison, multiple sequence alignment.
Phylogenetic analysis, genome comparison and molecular evolution.
Protein families.
Protein structure prediction.
Biological network analysis including gene networks and pathway analysis.
Transcriptomics and proteomics analysis including single-cell data analysis.
Analysis of other –omics data.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 18 | 1:00 | 18:00 | Lectures |
| Guided Independent Study | Assessment preparation and completion | 26 | 2:00 | 52:00 | Coursework for lab report |
| Guided Independent Study | Assessment preparation and completion | 18 | 1:00 | 18:00 | Coursework for essay |
| Guided Independent Study | Assessment preparation and completion | 8 | 1:00 | 8:00 | Coursework for formative assessment |
| Structured Guided Learning | Lecture materials | 6 | 1:00 | 6:00 | Key biological concepts – pre-recorded |
| Guided Independent Study | Directed research and reading | 48 | 0:30 | 24:00 | Lecture follow-up |
| Scheduled Learning And Teaching Activities | Practical | 16 | 1:00 | 16:00 | Practicals |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 16 | 0:30 | 8:00 | synchronous online session. Q re lectures |
| Guided Independent Study | Independent study | 50 | 1:00 | 50:00 | Background reading |
| Total | 200:00 |
Teaching Rationale And Relationship
Lectures will be used to introduce the learning material and for demonstrating the key concepts by example. Students are expected to follow-up lectures within a few days by re-reading and annotating lecture notes to aid deep learning.
This is a very practical subject, and it is important that the learning materials are supported by hands-on opportunities provided by practical classes. Students are expected to spend time on coursework outside timetabled practical classes.
Students aiming for 1st class marks are expected to widen their knowledge beyond the content of lecture notes through background reading.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Essay | 1 | M | 25 | Low stakes summative assessment: An essay on the bioinformatics approaches for a given biological problem. Max 1500 words |
| Practical/lab report | 1 | M | 75 | Summative assessment: A practical report on an advanced bioinformatics analysis exercise. Max 4000 words |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Report | 1 | M | Compulsory formative assessment: design of computational approach for bioinformatics analysis problem. Max 500 words |
Assessment Rationale And Relationship
The low stakes summative assessment will assess the student’s growing knowledge of the field.
The formative assessment will assess the students growing knowledge of bioinformatics algorithm design applied to the problem set in the summative assessment, providing feedback.
The summative assessment will assess the students’ ability to understand and apply the concepts of a range of a bioinformatics analytical techniques, including those described in the formative piece, and also their ability to design new approaches.
The practical reports are not typical essays. Where the word count is a good proxy for effort, the report should collect the results of the practical experiments that the students have performed, using the techniques covered throughout the module, contain a description of design decisions, an experimental plan and a report of experimental results, hence the requested 4000 word limit.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC8313's Timetable