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COMP5456: Introduction to Bioinformatics (2016 - Summer Main)

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Unit: COMP5456: Introduction to Bioinformatics [Not running in 2017] (6 CP)
Mode: Normal-Day
On Offer: Yes
Level: Postgraduate
Faculty/School: School of Computer Science
Unit Coordinator/s: A/Prof Charleston, Michael
Session options: Summer Main
Versions for this Unit:
Site(s) for this Unit:
Campus: Camperdown/Darlington
Pre-Requisites: None.
Prohibitions: COMP3456.
Brief Handbook Description: This unit brings together a wide range of skills that are routinely practised in bioinformatics, from the ‘hard’ subjects of mathematics, statistics and computer science, to the ‘soft’ subjects in the biological / health sciences and pharmacology. The unit covers the essentials of bioinformatics data gathering, manipulation, mining and storage that underpin bioinformatics research. It further provides additional practice in the graduate attributes of Research and Inquiry, Information Literacy and Communication through analysis of scientific research, use of large bioinformatics data sets, and writing of reports.
Assumed Knowledge: Some experience with basic programming (coding) in Java, C, C++ or Perl; Some proven ability in mathematical or information sciences (as evinced in the prerequisites); Some knowledge of molecular biology either through first year BIOL papers or MBLG1001.
Department Permission Department permission is required for enrollment in this session.
Lecturer/s: A/Prof Charleston, Michael
Timetable: COMP5456 Timetable
Time Commitment:
# Activity Name Hours per Week Sessions per Week Weeks per Semester
1 Laboratory 2.00 1 13
2 Lecture 2.00 1 13
3 Independent Study 5.00 1 13
T&L Activities: Lecture: Deliver and discuss course material

Independent Study: individual study of material, prescribed readings and assessment work

Attributes listed here represent the key course goals (see Course Map tab) designated for this unit. The list below describes how these attributes are developed through practice in the unit. See Learning Outcomes and Assessment tabs for details of how these attributes are assessed.

Attribute Development Method Attribute Developed
1. This unit provides additional practice in the graduate attribute of Research and Inquiry by requiring students to perform scientific investigations of their own, and by analysis of current bioinformatics research by case study. The unit will be taught by current researchers in bioinformatics and will therefore contain a component of current research. Design (Level 3)
Detailed understanding of a broad sampling of modern bioinformatics Engineering/IT Specialisation (Level 3)
Study of standard algorithms in computer science and how they are applies to for Life Science Maths/Science Methods and Tools (Level 2)
This UoS will enhance students’ skill in the graduate attribute of Communication, through writing reports and documentation and by presentation of results to the class or tutors. Communication (Level 3)
Students will be exposed to current software for bioinformatics in the labs Professional Conduct (Level 3)

For explanation of attributes and levels see Engineering & IT Graduate Outcomes Table.

Learning outcomes are the key abilities and knowledge that will be assessed in this unit. They are listed according to the course goal supported by each. See Assessment Tab for details how each outcome is assessed.

Design (Level 3)
1. Ability to design algorithms to solve novel bioinformatics problems
2. Ability to efficiently implement bioinformatics algorithms in computer applications
Engineering/IT Specialisation (Level 3)
3. General understanding of bioinformatics data, data formats and databases
Maths/Science Methods and Tools (Level 2)
4. Significance of computational biology and its impact on the study of life on Earth
5. Understanding the operation, advantages and limitations of a range of algorithms used in bioinformatics
Communication (Level 3)
6. Ability in technical writing to communicate complex ideas clearly
Professional Conduct (Level 3)
7. Knowledge of available software for bioinformatics
Assessment Methods:
# Name Group Weight Due Week Outcomes
1 Practical 1 No 2.50 Week 1
2 Practical 2 No 2.50 Week 1
3 Quiz No 20.00 Week 1 1, 3, 4,
4 Practical 3 No 2.50 Week 2
5 Practical 4 No 2.50 Week 2
6 Final Exam No 70.00 Exam Period 1, 3, 4, 5,
Assessment Description: Practical Exercises: Short computer-based assessments based on previous two days' course work.

Quiz: written quiz covering material in first half of the course.

Final Exam: Final written examination on all the course content, but with focus on that covered in the second half.
Grading:
Grade Type Description
Standards Based Assessment Final grades in this unit are awarded at levels of HD for High Distinction, DI (previously D) for Distinction, CR for Credit, PS (previously P) for Pass and FA (previously F) for Fail as defined by University of Sydney Assessment Policy. Details of the Assessment Policy are available on the Policies website at http://sydney.edu.au/policies . Standards for grades in individual assessment tasks and the summative method for obtaining a final mark in the unit will be set out in a marking guide supplied by the unit coordinator.
Special Conditions to Pass UoS It is a policy of the School of Information Technologies that in order to pass this unit, a student must achieve at least 40% in the written examination. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.
Policies & Procedures: IMPORTANT: School policy relating to Academic Dishonesty and Plagiarism.

In assessing a piece of submitted work, the School of IT may reproduce it entirely, may provide a copy to another member of faculty, and/or to an external plagiarism checking service or in-house computer program and may also maintain a copy of the assignment for future checking purposes and/or allow an external service to do so.

Other policies

See the policies page of the faculty website at http://sydney.edu.au/engineering/student-policies/ for information regarding university policies and local provisions and procedures within the Faculty of Engineering and Information Technologies.
Prescribed Text/s: Note: Students are expected to have a personal copy of all books listed.
Online Course Content: Content available through WebCT

Note that the "Weeks" referred to in this Schedule are those of the official university semester calendar https://web.timetable.usyd.edu.au/calendar.jsp

Week Description
Week 1 introduction to molecular biology and bioinformatics
Assessment Due: Practical 1
Assessment Due: Practical 2
Assessment Due: Quiz
Week 2 DNA mapping and brute force algorithms, the partial digest problem and the motif finding problem
Assessment Due: Practical 3
Assessment Due: Practical 4
Week 3 greedy algorithms and genome rearrangement
Week 4 dynamic programming and sequence comparison, the Manhattan tourist problem, pairwise sequence alignment and longest common subsequence problem
Week 5 sequence alignment under more general models, multiple sequence alignment
Week 6 divide and conquer algorithms, pairwise sequence alignment in linear space, speedups to alignment
Week 7 graph algorithms, Euler and Hamilton graphs, shortest superstring problem and fragment assembly, sequencing by hybridization
Week 8 combinatorial pattern matching, hashing, keyword and suffix trees
Week 9 repeat finding, BLAST & its derivatives
Week 10 clustering, microarray data, hierarchical and k-means clustering, corrupted cliques cliques problem, phylogenetic estimation
Week 11 hidden Markov models, CG islands, the decoding problem & Viterbi algorithm, profile HMM alignment
Week 12 randomized algorithms, Gibbs sampler for motif finding, local search methods
Week 13 Review
Exam Period Assessment Due: Final Exam

Course Relations

The following is a list of courses which have added this Unit to their structure.

Course Year(s) Offered
Bachelor of Computer Science and Technology (Honours) 2015, 2016, 2017
Bachelor of Computer Science and Technology (Honours) 2014 2013, 2014
Biomedical Engineering / Law 2013, 2014
Biomedical Engineering / Arts 2013, 2014
Biomedical Engineering / Commerce 2013, 2014
Biomedical Engineering / Medical Science 2013, 2014
Biomedical Engineering / Project Management 2013, 2014
Biomedical Engineering / Science 2013, 2014
Biomedical - Chemical and Biomolecular Major 2013, 2014, 2015
Biomedical - Electrical Major 2013, 2014
Biomedical - Information Technology Major 2013, 2014, 2015
Biomedical - Mechanical Major 2013, 2014, 2015
Biomedical - Mechatronics Major 2013, 2014, 2015
Biomedical Mid-Year 2016, 2017, 2018, 2019
Biomedical 2016, 2017, 2018, 2019
Biomedical / Arts 2015, 2016, 2017, 2018
Biomedical / Commerce 2015
Biomedical / Medical Science 2015
Biomedical / Music Studies 2016, 2017
Biomedical / Project Management 2015, 2016, 2017
Biomedical /Science 2015, 2016, 2017, 2018
Biomedical/Science (Health) 2018
Biomedical - Electrical Major 2015
Biomedical / Law 2015, 2016, 2017, 2018
Bachelor of Information Technology 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Arts 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Commerce 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Medical Science 2015, 2016, 2017
Bachelor of Information Technology/Bachelor of Science 2015, 2016, 2017
Bachelor of Information Technology (Computer Science) 2014 and earlier 2011, 2012, 2013, 2014
Information Technology (Computer Science)/Arts 2012, 2013, 2014
Information Technology (Computer Science) / Commerce 2012, 2013, 2014
Information Technology (Computer Science) / Medical Science 2012, 2013, 2014
Information Technology (Computer Science) / Science 2012, 2013, 2014
Information Technology (Computer Science) / Law 2012, 2013, 2014
Bachelor of Information Technology (Information Systems) 2014 and earlier 2013, 2014
Information Technology (Information Systems)/Arts 2012, 2013, 2014
Information Technology (Information Systems) / Commerce 2013, 2014
Information Technology (Information Systems) / Medical Science 2012, 2013, 2014
Information Technology (Information Systems) / Science 2012, 2013, 2014
Information Technology (Information Systems) / Law 2012, 2013, 2014
Bachelor of Information Technology/Bachelor of Laws 2015, 2016, 2017
Graduate Certificate in Information Technology 2015, 2016, 2017, 2018, 2019
Graduate Certificate in Information Technology Management 2015, 2016, 2017, 2018, 2019
Graduate Diploma in Computing 2015, 2016, 2017, 2018, 2019
Graduate Diploma in Health Technology Innovation 2015, 2016, 2017, 2018, 2019
Graduate Diploma in Information Technology 2015, 2016, 2017, 2018, 2019
Graduate Diploma in Information Technology Management 2015, 2016, 2017, 2018, 2019
Graduate Certificate in Information Technology (till 2014) 2012, 2013, 2014
Graduate Diploma in Information Technology (till 2014) 2012, 2013, 2014
Master of Engineering 2014, 2015, 2016, 2017, 2018, 2019
Master of Health Technology Innovation 2015, 2016, 2017, 2018, 2019
Master of Information Technology 2015, 2016, 2017, 2018, 2019
Master of Information Technology Management 2015, 2016, 2017, 2018, 2019
Master of IT/Master of IT Management 2015, 2016, 2017, 2018, 2019
Master of Information Technology (till 2014) 2014

Course Goals

This unit contributes to the achievement of the following course goals:

Attribute Practiced Assessed
Design (Level 3) Yes 24.17%
Engineering/IT Specialisation (Level 3) Yes 24.17%
Maths/Science Methods and Tools (Level 2) Yes 41.67%
Communication (Level 3) Yes 0%
Professional Conduct (Level 3) Yes 0%

These goals are selected from Engineering & IT Graduate Outcomes Table which defines overall goals for courses where this unit is primarily offered. See Engineering & IT Graduate Outcomes Table for details of the attributes and levels to be developed in the course as a whole. Percentage figures alongside each course goal provide a rough indication of their relative weighting in assessment for this unit. Note that not all goals are necessarily part of assessment. Some may be more about practice activity. See Learning outcomes for details of what is assessed in relation to each goal and Assessment for details of how the outcome is assessed. See Attributes for details of practice provided for each goal.