|Delivery Type||Delivery length / details|
|Lecture||10 x 2hour lectures|
|Practical||5 x 2hour practicals|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Practical programming assignment 1||40%|
|Semester Assessment||Practical programming assignment 2||60%|
|Supplementary Assessment||Resubmission of failed/non-submitted coursework components or ones of equivalent value||100%|
On successful completion of this module students should be able to:
write code to perform common bioinformatics tasks
query/modify a data file or a database
make use of data in XML format
retrieve information from popular bioinformatics APIs such as ENSEMBL and BLAST
This module aims to equip the students with programming skills for information retrieval, data manipulation, data/model/knowledge storing and sharing, and high performance computing.
This module will emphasise use of the scripting language, Python to carry out tasks in Bioinformatics and to manage data using specialist Bioinformatics tools as well as conventional files and database.
2. Reading and writing files. Examples of bioinformatics file formats e.g. CSV, FASTA, FASTQ, SAM, etc. Example programming tasks collecting basic information from these files, reformatting files. General familiarity and experience using Python.
3. Databases: Examining database structure (tables, keys, relations). Interfacing to databases using SQL and Python. Basic design of databases.
4. XML: structure, parsing, correctness and schema. SBML and other examples.
5. Using remote APIs (e.g. ENSEMBL or BLAST) to query online bioinformatics resources
|Skills Type||Skills details|
|Application of Number||Inherent in the study of programming for bioinformatics|
|Improving own Learning and Performance||Inherent in the module.|
|Information Technology||Programming, interfacing with online data systems|
|Personal Development and Career planning||Gives students practical skills for a career in this field|
|Problem solving||Identifying and using programming techniques to solve problems in Computational Biology|
|Research skills||Problem analysis, data resource discovery, experimental design, data analysis|
|Subject Specific Skills|
This module is at CQFW Level 7