Bioinformatics
Master of Science in Bioinformatics
These resolutions must be read in conjunction with applicable University By-laws, Rules and policies including (but not limited to) the University of Sydney (Coursework) Rule 2000 (the 'Coursework Rule'), the Resolutions of the Faculty, the University of Sydney (Student Appeals against Academic Decisions) Rule 2006 (as amended) and the Academic Board policies on Academic Dishonesty and Plagiarism.
Course resolutions
1 Course codes
|
Code |
Course and stream title |
|---|---|
| LG027 |
Graduate Certificate in Bioinformatics |
| LF043 |
Graduate Diploma in Bioinformatics |
| LC055 |
Master of Science in Bioinformatics |
2 Attendance pattern
0.
The attendance pattern for these courses is full time or part time according to candidate choice, except the Graduate Certificate in Bioinformatics that is available part time only.
3 Master's type
4 Embedded courses in this sequence
(2)
Providing candidates satisfy the admission requirements for each stage, a candidate may progress to the award of any course in this sequence. Only the highest award completed will be conferred.
5 Admission to candidature
(1)
In exceptional circumstances the Dean may admit applicants to the Graduate Certificate or Graduate Diploma without the following qualifications, but whose evidence of experience and achievement is deemed by the Dean to be equivalent.
(2)
With approval from the Dean available places will be offered to qualified applicants according to the following admissions criteria:
(3)
Admission to the Graduate Certificate in Bioinformatics requires a Bachelor of Science with a molecular life science or information technology major from the University of Sydney, or equivalent qualification.
(a)
a Bachelor of Science with a molecular life science or information technology major from the University of Sydney, or equivalent qualification; or
(b)
completion of the embedded graduate certificate in this discipline from the University of Sydney, or equivalent qualification.
(a)
a Bachelor of Science with a molecular life science or information technology major with a credit average from the University of Sydney or equivalent qualification; or
(b)
a Bachelor of Science with Honours with a molecular life science or information technology major from the University of Sydney, or equivalent qualification; or
(c)
completion of the embedded graduate diploma in this discipline from the University of Sydney, or equivalent qualification.
6 Requirements for award
(1)
The units of study that may be taken for these awards are set out in the table for Bioinformatics postgraduate courses. With the approval of the Dean and the program coordinator, candidates for the graduate diploma or master's degree, with special aims or interests, may be allowed to substitute up to 12 credit points with relevant postgraduate units from outside the table.
(2)
Candidates from an Information Technology background must complete a set of units of study listed in Part A (Information Technology background) of the table. Candidates from a Life Sciences background must complete a set of units of study listed in Part B (Life Sciences background) of the table.
(a)
To qualify for the Graduate Certificate in Bioinformatics a candidate must complete 24 credit points of core units of study.
(b)
To qualify for the Graduate Diploma in Bioinformatics a candidate must complete 36 credit points, including:
(c)
To qualify for the Master of Science in Bioinformatics coursework pathway a candidate must complete 48 credit points, including:
(d)
Subject to the availability of supervision and suitable projects, candidates with a credit average in 24 credit points of study from the degree may be admitted to the research pathway.
(e)
To qualify for the Master of Science in Bioinformatics research pathway a candidate must complete 48 credit points, including:
(a)
To qualify for the Graduate Certificate in Bioinformatics a candidate must complete 24 credit points of core units of study.
(b)
To qualify for the Graduate Diploma in Bioinformatics a candidate must complete 36 credit points of study, including:
(c)
To qualify for the Master of Science in Bioinformatics coursework pathway a candidate must complete 48 credit points, including:
Course overview
The Graduate Certificate in Applied Science (Bioinformatics), Graduate Diploma in Applied Science (Bioinformatics) and Master of Applied Science (Bioinformatics) are articulated award courses that provide a professional qualification to biologists and computer scientists working in industry, research and education.
The award program brings together the disciplines of computer science, statistics and the life sciences, developing and enhancing skills in bioinformatics. Students with little background in molecular biology who want to extend their understanding of the biosciences, statistics and bioinformatics follow Stream A. Students with a strong background in molecular biology who want to study bioinformatics, statistics and computer science follow Stream B.
The program has core and optional units of study to satisfy both of these requirements and will produce graduates with skills in the disciplines that underpin bioinformatics and in bioinformatics itself. Graduates from the Bioinformatics program will be proficient in molecular biology, genetics and bioinformatics. (Biology graduates who want to learn about computer programming are directed to the Graduate Diploma in Computing).
Candidates will normally commence their study in Semester 1, except with the permission of the Dean.
Course outcomes
The aim of this articulated coursework program is to provide students with a coordinated approach to bioinformatics, thus developing expertise to perform and develop the analysis of biological data with underlying competencies in the life sciences, computer science and statistics. Upon completion of the graduate certificate, graduate diploma or master's, graduates will have a broad understanding of the topic of bioinformatics. In addition, the master's will provide the option of experience in carrying out and completing a research project and report.
Bioinformatics postgraduate coursework degree table
Units of study listed in the table as optional are recommended; other Information Technology units of study are also available with approval from the the Program Coordinator.
Units of study listed as compulsory for a particular degree or stream do not need department permission for enrolment.
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition | Session |
|---|---|---|---|
Stream A (Computer Scientist) |
|||
Core Units |
|||
| All candidates must complete all the following units. | |||
| BIOL5001 Molecular Genetics and Inheritance |
6 |
Note: Department permission required for enrolment Department permission not required for Stream A Bioinformatics students. |
Semester 1 |
| BIOL5002 Bioinformatics: Sequences and Genomes |
6 | N BIOL3027, BIOL3927 |
Semester 2 |
| MOBT5201 Applied Molecular Biotech A (Theory) |
6 | N BCHM3098, BCHM5001, MOBT5101 |
Semester 1 |
| STAT5001 Applied Statistics for Bioinformatics |
6 | Semester 1 |
|
Elective units |
|||
| Graduate Diploma candidates must complete 12 credit points from the following units. Masters coursework pathway candidates must complete 24 credit points from the following units. Masters research pathway candidates must complete 6 credit points from the following units. | |||
| COMP5028 Object-Oriented Design |
6 | A Intermediate level of object oriented programming such as Java N INFO3220 |
Semester 1 |
| COMP5211 Algorithms |
6 | Semester 1 Semester 2 |
|
| COMP5318 Knowledge Discovery and Data Mining |
6 | A COMP5138 and familiarity with basic statistics |
Semester 1 |
| COMP5424 Information Technology in Biomedicine |
6 | A Basic programming skills |
Semester 1 |
| COMP5426 Parallel and Distributed Computing |
6 | A Equivalent of COMP5116 |
Semester 1 |
| COMP5456 Computational Methods for Life Sciences |
6 | N COMP3456 |
Semester 2 |
| MCAN5104 Image Analysis |
6 | Int April Int Sept |
|
| BETH5000 Core Concepts in Bioethics |
6 | A A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, history, or other relevant field, or by special permission. A limited number of students may be granted permission to take this unit during their honours year. |
Semester 2 |
| BETH5201 Ethics and Biotech: Genes and Stem Cells |
6 | A A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, history, or other relevant field, or by special permission. A limited number of students may be granted permission to take this unit during their honours year. |
Semester 1 |
Additional Core Units: Masters Research Pathway Only |
|||
| Masters research pathway candidates must complete all of the following units. | |||
| NB: Entry to the Masters Research stream is by invitation only. | |||
| BINF5002 Bioinformatics Research Project A |
6 | C BINF5003, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Note: Department permission required for enrolment |
Semester 2 |
| BINF5003 Bioinformatics Research Project B |
6 | C BINF5002, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Note: Department permission required for enrolment |
Semester 2 |
| MCAN5210 Research Methodology |
6 | C MCAN5203 Project and Report Part C Optional for Masters (non research path) |
Semester 2 |
Stream B (Life Scientist) |
|||
Core Units |
|||
| All candidates must complete all the following units. | |||
| BIOL5002 Bioinformatics: Sequences and Genomes |
6 | N BIOL3027, BIOL3927 |
Semester 2 |
| COMP5213 Computer and Network Organisation |
6 | Semester 1 Semester 2 |
|
| MOBT5201 Applied Molecular Biotech A (Theory) |
6 | N BCHM3098, BCHM5001, MOBT5101 |
Semester 1 |
| STAT5001 Applied Statistics for Bioinformatics |
6 | Semester 1 |
|
Additional Core Unit: Graduate Diploma and Masters Only |
|||
| Candidates in the Graduate Diploma and Masters coursework and research pathways must complete the following unit. | |||
| COMP5212 Software Construction |
6 | Semester 1 |
|
Elective Units |
|||
| Graduate diploma candidates must complete 6 credit points from the following units. Masters coursework pathway candidates must complete 18 credit points from the following units. | |||
| COMP5206 Introduction to Information Systems |
6 | N INFO5210 |
Semester 1 Semester 2 |
| COMP5211 Algorithms |
6 | Semester 1 Semester 2 |
|
| COMP5214 Software Development in Java |
6 |
Note: Department permission required for enrolmentin the following sessions:Semester 1, |
Semester 1 Semester 2 |
| COMP5456 Computational Methods for Life Sciences |
6 | N COMP3456 |
Semester 2 |
| MCAN5104 Image Analysis |
6 | Int April Int Sept |
|
| BETH5201 Ethics and Biotech: Genes and Stem Cells |
6 | A A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, history, or other relevant field, or by special permission. A limited number of students may be granted permission to take this unit during their honours year. |
Semester 1 |
Additional Core Units: Masters Research Pathway Only |
|||
| Masters research stream students must complete all of the following units. | |||
| NB: Entry to the Masters Research stream is by invitation only | |||
| MCAN5210 Research Methodology |
6 | C MCAN5203 Project and Report Part C Optional for Masters (non research path) |
Semester 2 |
| BINF5002 Bioinformatics Research Project A |
6 | C BINF5003, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Note: Department permission required for enrolment |
Semester 2 |
| BINF5003 Bioinformatics Research Project B |
6 | C BINF5002, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Note: Department permission required for enrolment |
Semester 2 |
Unit of study descriptions
BETH5000 Core Concepts in Bioethics
Credit points: 6 Session: Semester 2 Classes: 13 x 2 hr seminars Assumed knowledge: A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, history, or other relevant field, or by special permission. Assessment: 1x750 wd review (15%) and 1x1500wd essay (35%) and 1x200-2500 wd essay (50%)
Note: A limited number of students may be granted permission to take this unit during their honours year.
This unit of study provides a broad overview of the primary issues in, and theoretical approaches to, bioethics. Following an introduction to the history of bioethics and review of the major theoretical approaches to applied ethics, central debates in bioethics surrounding doctor-patient relationships, informed consent, privacy/confidentiality, research ethics, abortion, euthanasia, genetics, cloning, stem cell research, justice and distribution of health care resources, etc., are examined. In addition to classical cases and traditional theoretical perspectives, emerging topics and alternative perspectives are explored. The unit concludes with the topic of global public health and socio-political critique(s) of the discipline of bioethics itself. Learning activities will include seminars, small group sessions, and project work.
BETH5201 Ethics and Biotech: Genes and Stem Cells
Credit points: 6 Session: Semester 1 Classes: 6 x 2hr seminars
1 x 8 hr intensive Assumed knowledge: A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, history, or other relevant field, or by special permission. Assessment: 3 Tutorial assessments - 400 wds each (3x 10%); 1 x 1200-1500 wd essay (30%); 1 x 2200 - 2500 wd essay (40%)
Note: A limited number of students may be granted permission to take this unit during their honours year.
This unit introduces students to the broader social/political, ethical/philosophical and legal/regulatory issues that underlie genetics, stem cell research and the emerging biotechnologies. The unit will provide a brief overview of the relevant science before considering scientific, cultural and religious understandings of life and human identity. The second part of the unit will review the political, regulatory and commercial context of biotechnology and the control of information. Students will then review the history of genetics and eugenics and the ethical issues that arise in clinical and population genetics, stem cell research and cloning. The final part of the unit will explore the boundaries of research and knowledge and the issues raised by emerging biotechnologies, such as nanotechnology and proteomics. Learning activities will include an intensive seminar program, small group sessions and reading. Students will be able to concentrate on stem cell research, clinical or molecular genetics or other biotechnologies according to their clinical and scientific interests and experience.
BINF5002 Bioinformatics Research Project A
Credit points: 6 Teacher/Coordinator: Dr N Lo Session: Semester 2 Classes: Meetings by arrangement with the supervisor Corequisites: BINF5003, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Assessment: 1 x project plan (up to 4 A4 pages) (10%), 1x20 minute research seminar (including question time) (30%), 1 x final report (3000-5000 words) (60%).
Note: Department permission required for enrolment
BINF5002 comprises the commencement of a research project on a topic with significant emphasis on the use of bioinformatics tools to address important questions in the areas of biology, biochemistry, mathematics and statistics, computer science, crop and veterinary sciences, and medical science. Students will be working with an appointed supervisor from the Faculties of Agriculture, Science, Veterinary Science, and Medicine or from industry under the guidelines of the convenor. Students will commence a small research project in an area agreed by the student, the supervisor and the convenor. Research experience is highly valued by prospective employers as it shows a willingness and ability to undertake independent, as well as guided, research in bioinformatics. The project is not conducted in the way of contact hours per week for a semester. Rather, the student is expected to work in a continuous manner throughout the semester.
BINF5003 Bioinformatics Research Project B
Credit points: 6 Teacher/Coordinator: Dr N Lo Session: Semester 2 Classes: Meetings by arrangement with the supervisor Corequisites: BINF5002, BIOL5001, BIOL5002, MOBT5201 and STAT5001 Assessment: 1 x Project (up to 4 A4 pages) (10%), 1 x 20 minute Research Seminar (30%), 1 x Final Report (3000-5000) (60%).
Note: Department permission required for enrolment
BINF5003 comprises the continuation of a research project commenced in BINF5002.
BIOL5001 Molecular Genetics and Inheritance
Credit points: 6 Teacher/Coordinator: Dr Jenny Saleeba Session: Semester 1 Classes: 2-3 tutorials per week. Assessment: Formal exam, quizzes (100%)
Note: Department permission required for enrolment
Note: Department permission not required for Stream A Bioinformatics students.
The fundamentals of inheritance and applications of molecular genetics will be covered. At the completion of the Unit, students will be able to recognise the most common modes of inheritance, understand the fundamentals of linkage analysis, be familiar with common genome structures, be familiar with modes of transmission and mechanisms of change in genetic material, be familiar with the genetic mechanisms behind complex biological systems, understand basic methods in recombinant DNA technology, be adept at applying genetics to solving problems in biology and understand the fundamentals of quantitative and population genetics.
BIOL5002 Bioinformatics: Sequences and Genomes
Credit points: 6 Teacher/Coordinator: Dr Neville Firth Session: Semester 2 Classes: 1 lecture or tutorial per week, 1 three hour practical per fortnight. Prohibitions: BIOL3027, BIOL3927 Assessment: Formal exam, projects (100%)
Bioinformatics - the application of computers to life sciences, and genomics - the study of biology at the genome-wide scale, are revolutionising basic and applied biological sciences in the 21st century. The unit focuses on the application of bioinformatics to the storage, retrieval and analysis of biological information, principally in the form of nucleotide and amino acid sequences. An extensive practical component emphasises the development of hands-on skills in the use of bioinformatics technologies. Students will gain an appreciation of the significance and potential of bioinformatics and genomics in contemporary life sciences; an awareness of the breadth of bioinformatics resources and applications, including non-sequence-based biological information; skills and experience in the use of a core set of programs and databases for nucleotide and amino acid sequence analysis and phylogenetic reconstruction; a basic understanding of the theoretical foundation and underlying assumptions of the programs, and their relative strengths/limitations; and, competence in the evaluation of output from the programs in appropriate biological context.
COMP5028 Object-Oriented Design
Credit points: 6 Session: Semester 1 Classes: One 2 hour lecture and one 1 hour tutorial per week. Prohibitions: INFO3220 Assumed knowledge: Intermediate level of object oriented programming such as Java Assessment: Quiz (10%), lab skills (10%), assignments(30%), final written exam (50%).
This unit introduces essential object-oriented design methods and language mechanisms, especially the principles of modelling through Rational Unified Process and agile processes using Unified Modeling Language (UML) and C++, both of which are industry standard. Students work in small groups to experience the process of object-oriented analysis, object-oriented design, implementation and testing by building a real-world application. C++ is used as the implementation language and a special emphasis is placed on those features of C++ that are important for solving real-world problems. Advanced software engineering features, including exceptions and name spaces are thoroughly covered. Note: The lectures of this unit are co-taught with the corresponding INFO3220.
COMP5206 Introduction to Information Systems
Credit points: 6 Session: Semester 1,Semester 2 Classes: One 2 hour lecture and one 1 hour tutorial per week. Prohibitions: INFO5210 Assessment: Quiz (10%), Assignment (40%), Final Exam (50%)
This unit will provide a comprehensive introduction to the field of information systems from an organisational perspective. The critical role of information and knowledge management will be emphasised from both conceptual and practical standpoints. Methods and techniques for analysing systems and eliciting user requirements will be discussed. Key topics covered will include:
* Basic Information Systems Concepts
* Systems approach and systems thinking
* E-Business and E-Commerce
* Data and Knowledge Management
* Systems Analysis and Development Methodologies
* Ethical, Legal and Social Aspects of Information technologies
* Web 2.0 and Social Computing
Objectives: Students who successfully complete this unit will be able to:
1. Develop a good understanding of important information concepts,
2. Deep understanding of the systems approach and its applicability.
3. Develop skills to perform systems analysis in contemporary systems environments
4. Understanding of major conceptual and technological developments in Information Systems
* Basic Information Systems Concepts
* Systems approach and systems thinking
* E-Business and E-Commerce
* Data and Knowledge Management
* Systems Analysis and Development Methodologies
* Ethical, Legal and Social Aspects of Information technologies
* Web 2.0 and Social Computing
Objectives: Students who successfully complete this unit will be able to:
1. Develop a good understanding of important information concepts,
2. Deep understanding of the systems approach and its applicability.
3. Develop skills to perform systems analysis in contemporary systems environments
4. Understanding of major conceptual and technological developments in Information Systems
COMP5211 Algorithms
Credit points: 6 Session: Semester 1,Semester 2 Classes: One 2 hour lectures and one 1 hour tutorial per week. Assessment: Assignment (50%), Final Exam (50%)
The study of algorithms is a fundamental aspect of computing. This unit of study covers data structures, algorithms, and gives an overview of the main ways of thinking used in IT from simple list manipulation and data format conversion, up to shortest paths and cycle detection in graphs. The objective of the unit are to teach basic concepts in data structure, algorithm, dynamic programming and program analysis. Students will gain essential knowledge in computer science.
COMP5212 Software Construction
Credit points: 6 Session: Semester 1 Classes: One 2 hour lecture and one 2 hour tutorial per week. Assessment: Assignment (30%), Quiz (30%), Final Exam (40%)
This unit gives an introduction to C and UNIX, and provides an introduction to parallel programming of modern multi-core architectures using C. The unit also introduces a CUDA, which is an extension of C for massively data-parallel architectures such as GPGPUs.
In this unit of study elementary methods for developing robust, efficient and re-usable parallel software will be covered. The unit is taught in C, in a Unix environment. Specific coding topics include memory management, the pragmatic aspects of implementing data structures such as lists and managing concurrent threads. In the lab, debugging tools and techniques are discusse. Emphasis is placed on using common Unix tools to manage aspects of the software construction process, such as make. The subject is taught from a practical and theoretical viewpoint and it includes a considerable amount of programming practice, using existing tools.
In this unit of study elementary methods for developing robust, efficient and re-usable parallel software will be covered. The unit is taught in C, in a Unix environment. Specific coding topics include memory management, the pragmatic aspects of implementing data structures such as lists and managing concurrent threads. In the lab, debugging tools and techniques are discusse. Emphasis is placed on using common Unix tools to manage aspects of the software construction process, such as make. The subject is taught from a practical and theoretical viewpoint and it includes a considerable amount of programming practice, using existing tools.
COMP5213 Computer and Network Organisation
Credit points: 6 Session: Semester 1,Semester 2 Classes: One 2 hour lecture and one 1 hour tutorial per week. Assessment: Assignment (40%), Final Exam (60%)
This unit of study provides an overview of hardware and system software infrastructure including: compilers, operating systems, device drivers, network protocols, etc. It also includes user-level Unix skills and network usability. The objectives are to ensure that on completion of this unit students will have developed an understanding of compilers, operating systems, device drivers, network protocols, Unix skills and network usability.
COMP5214 Software Development in Java
Credit points: 6 Session: Semester 1,Semester 2 Classes: One 2 hour lecture and one 1 hour tutorial per week. Assessment: Assignment (75%), Lab Skills (25%)
Note: Department permission required for enrolmentin the following sessions:Semester 1
This unit of study introduces software development methods, where the main emphasis is on careful adherence to a process. It includes design methodology, quality assurance, group work, version control, and documentation. It will suit students who do not come from a programming background, but who want to learn the basics of computer software.
Objectives: This unit of study covers systems analysis, a design methodology, quality assurance, group collaboration, version control, software delivery and system documentation.
Objectives: This unit of study covers systems analysis, a design methodology, quality assurance, group collaboration, version control, software delivery and system documentation.
COMP5318 Knowledge Discovery and Data Mining
Credit points: 6 Session: Semester 1 Classes: (Lec 2hrs & Prac 1hr) per week Assumed knowledge: COMP5138 and familiarity with basic statistics Assessment: Quiz (10%), Assignment (15%), Presentation/Seminar (15%), Final Exam (60%)
Knowledge discovery is the process of extracting useful knowledge from data. Data mining is a discipline within knowledge discovery that seeks to facilitate the exploration and analysis of large quantities of data, by automatic or semiautomatic means. This subject provides a practical and technical introduction to knowledge discovery and data mining.
Objectives: Topics to be covered include problems of data analysis in databases, discovering patterns in the data, and knowledge interpretation, extraction and visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques: clustering, classification, prediction, estimation, affinity grouping, description and scientific visualisation.
Objectives: Topics to be covered include problems of data analysis in databases, discovering patterns in the data, and knowledge interpretation, extraction and visualisation. Also covered are analysis, comparison and usage of various types of machine learning techniques and statistical techniques: clustering, classification, prediction, estimation, affinity grouping, description and scientific visualisation.
COMP5424 Information Technology in Biomedicine
Credit points: 6 Session: Semester 1 Classes: (Lec 2hrs & Tut 1hr) per week Assumed knowledge: Basic programming skills Assessment: Lab Skills (10%), Assignment (20%), Quiz (10%), Final Exam (60%)
Information technology (IT) has significantly contributed to the research and practice of medicine, biology and health care. The IT field is growing enormously in scope with biomedicine taking a lead role in utilizing the evolving applications to its best advantage. The goal of this unit of study is to provide students with the necessary knowledge to understand the information technology in biomedicine. The major emphasis will be on the principles associated with biomedical digital imaging systems and related biomedicine data processing, analysis, visualization, registration, modelling, compression, management, communication and security. Specialist areas such as Picture Archiving and Communication Systems (PACS), computer-aided diagnosis (CAD), content-based medical image retrieval (CBMIR), and ubiquitous m-Health, etc. will be addressed. A broad range of practical integrated clinical applications will be also elaborated.
COMP5426 Parallel and Distributed Computing
Credit points: 6 Session: Semester 1 Classes: (Lec 2hrs & Prac 1hr) per week. Assumed knowledge: Equivalent of COMP5116 Assessment: Assignment (30%), Quiz (10%), Final Exam (60%)
This unit is intended to introduce and motivate the study of high performance computer systems. The student will be presented with the foundational concepts pertaining to the different types and classes of high performance computers. The student will be exposed to the description of the technological context of current high performance computer systems. Students will gain skills in evaluating, experimenting with, and optimizing the performance of high performance computers. The unit also provides students with the ability to undertake more advanced topics and courses on high performance computing.
COMP5456 Computational Methods for Life Sciences
Credit points: 6 Session: Semester 2 Classes: One 2 hour lecture, one 1 hour tutorial and one 2 hour lab per week. Prohibitions: COMP3456 Assessment: Quiz (10%), Assignment (20%), Final Exam (70%)
This unit brings together a wide range of skils 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. It covers the essentials of bioinformatics data gathering, manipulation, mining and storage that underpin bioinformatics research, and 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.
MCAN5104 Image Analysis
Credit points: 6 Teacher/Coordinator: A/Prof. Allan Jones Session: Int April,Int Sept Classes: 10 one hour lectures, 10 two hour practicals over a one week period. Assessment: Eight practical reports (50%), 1 three part mathematical assignment (20%), 1 in-depth assignment of 2500 word length on a relevant topic (30%).
This unit of study covers the nature and processing of images and the extraction of quantitative data from them. Participants will develop a sound working knowledge of both traditional stereology techniques and modern digital image processing and analysis. Emphasis is placed on an understanding of both the strengths and the limitations that are inherent in image data, and the technology applied to it. Topics in this module include: a general review of image acquisition, filters and transforms, segmentation methods, calibration of hardware for analysis, extraction of simple features from images, advanced feature extraction from images, limitations of measurement and a general overview of stereology, including geometric probability, density estimation and sampling.
MCAN5210 Research Methodology
Credit points: 6 Teacher/Coordinator: A/Prof. Julie Cairney and Dr Rongkun Zheng Session: Semester 2 Classes: Thirteen hours of lectures, one hour student presentation, four hours of tutorials/practicals. Corequisites: MCAN5203 Project and Report Part C Assessment: Risk assessment (10%), written research proposal (30%), written experimental plan (30%), worked exercises in data analysis (30%).
Note: Optional for Masters (non research path)
This unit covers the principles and practice of research methodology. Topics included: literature and database searches; citing and referencing; research proposals; safety, risk assessment and ethics; experimental design and documentation; statistics, errors and data analysis; and written and oral communication.
MOBT5201 Applied Molecular Biotech A (Theory)
Credit points: 6 Teacher/Coordinator: Dr Neville Firth Session: Semester 1 Classes: One 2 hour lecture and one 1 hour tutorial per week. Prohibitions: BCHM3098, BCHM5001, MOBT5101 Assessment: One 2 hour theory exam (70%) and in semester assessments (30%).
This unit of study comprises the lecture component of MOBT5101.
STAT5001 Applied Statistics for Bioinformatics
Credit points: 6 Session: Semester 1 Classes: one three hour seminar per week Assessment: computer exam and lab reports (100%)
This is an introduction to statistics and data analysis used in Bioinformatics and many other areas of Biology. It aims to give an understanding of the concepts and the use of a major scientific statistical package, R. In addition to an introduction to ideas of analysis of data and statistical tests the unit will introduce ideas of simulation in resampling and the methods of clustering and classification of particular importance in Bioinformatics.