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BIOT8007 - Bioinformatics 1

Title:Bioinformatics 1
Long Title:Bioinformatics 1
Module Code:BIOT8007
Credits: 5
NFQ Level:Advanced
Field of Study: Biotechnology
Valid From: Semester 1 - 2011/12 ( September 2011 )
Module Delivered in 1 programme(s)
Module Coordinator: BRENDAN O CONNELL
Module Author: HUGH MC GLYNN
Module Description: This module provides an introduction to bioinformatics – specifically the use of computational models and databases to manage the vast amount of sequence data generated by modern genomics and metagenomics projects.
Learning Outcomes
On successful completion of this module the learner will be able to:
LO1 Interpret information from a range of database sources and apply strategies for the analysis and management of sequence data.
LO2 Critically evaluate the strengths and weaknesses of the tools available for genome analysis.
LO3 Recommend suitable options for a database search using BLAST and FASTA and explain the significance of the results.
LO4 Synthesise multiple sequence alignments and highlight the significant features of the alignment using an alignment editor.
LO5 Predict protein structural features using motif and profile databases.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named CIT module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.

No requirements listed
No Co Requisites listed

Module Content & Assessment

Indicative Content
Introduction to Bioinformatics
An introduction to bioinformatics and the use of online resources in modern molecular biology.
DNA and protein sequence databases
A comprehensive overview of the main sequences databases and the information retrieval systems which provide access to these databases.
Nucleic acid sequence analysis
A detailed overview of the online tools available for genome sequence analysis.
Sequence alignments and database searches
An overview of local and global alignment algorithms for sequence comparisons.
Protein function prediction
An analysis of motif and profile databases to predict protein function, including hydrophobicity analysis, identification of transmembrane helices, leader sequences, coils etc.
Protein structure prediction
An overview of threading algorithms and fold prediction as well as homology modelling and 3D structure prediction using Deep View.
Assessment Breakdown%
Course Work100.00%
Course Work
Assessment Type Assessment Description Outcome addressed % of total Assessment Date
Multiple Choice Questions 50 Question MCQ with negative marking 1,2,3,4,5 70.0 Sem End
Practical/Skills Evaluation in silico problem based assessments with detailed write-ups to be submitted online. 1,2,3,4,5 30.0 Every Week
No End of Module Formal Examination
Reassessment Requirement
Repeat examination
Reassessment of this module will consist of a repeat examination. It is possible that there will also be a requirement to be reassessed in a coursework element.

The institute reserves the right to alter the nature and timings of assessment


Module Workload

Workload: Full Time
Workload Type Workload Description Hours Frequency Average Weekly Learner Workload
Lecture Face to face and blended learning 2.0 Every Week 2.00
Lab in silico problem based learning 2.0 Every Week 2.00
Independent & Directed Learning (Non-contact) eportfolio 3.0 Every Week 3.00
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
This module has no Part Time workload.

Module Resources

Recommended Book Resources
  • Lesk, Introduction to Bioinformatics
Supplementary Book Resources
  • Zvelebil and Boum, Understanding Bioinformatics
This module does not have any article/paper resources
This module does not have any other resources

Module Delivered in

Programme Code Programme Semester Delivery
CR_SCMPB_9 Master of Science in Computational Biology 1 Elective

Cork Institute of Technology
Rossa Avenue, Bishopstown, Cork

Tel: 021-4326100     Fax: 021-4545343
Email: help@cit.edu.ie