Students
CBMS793 – Research Topic: Advanced Biomolecular Analysis
2014 – S2 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Mark Molloy
Contact via mark.molloy@mq.edu.au
Instructor
Nicki Packer
Contact via nicki.packer@mq.edu.au
Instructor
Ian Paulsen
Contact via ian.paulsen@mq.edu.au
Instructor
Bhumika Shah
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| Credit points |
Credit points
4
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| Prerequisites |
Prerequisites
Admission to MRes
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit addresses some advanced methods of analysis utilised in the biomolecular sciences. Biomolecular sciences spans the study of individual molecular structures and biochemical reactions to also encompass the 'omics' sciences of genomics, proteomics, metabolomics and glycomics. These sciences all generate large and complex datasets that require specialized programs and methods to assemble and analyse. The analyses are challenging, as they not only require a good knowledge of biochemistry, molecular biology, and cell and developmental biology, but also an understanding of limitations of both the programs and the data quality. This unit will provided a background to the data acquisition methods, quality control of the datasets, and analysis methods within a number of these areas. Most importantly it will provide hands-on experience in the analysis of real large-scale datasets and the correct use of the appropriate analysis tools available.
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Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Process the datasets to give a broad overview of data in terms of size, quality and utility for further analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
General Assessment Information
- All written work must be submitted via the assignments box located in the Science Centre (E7A 101). Submission must include a completed and signed cover sheet stapled to the front cover.
- Late submissions will be penalised with 10% loss of the maximum mark for each day past the deadline. More than 5 days late will result in 0 marks awarded unless Disruption to Studies application has been requested.
- If there is any medical reason why you cannot submit work on time you should lodge a Disruption of Studies application, otherwise your mark will be penalized for lateness.
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| Quantitative MS techniques | 10% | 21st August |
| Molecular Graphics Structures | 10% | 18th Sept 2014 |
| Proteomics Data Report | 20% | 26th Sept 2014 |
| Genomics Data Presentation | 20% | 24th Oct |
| Glycomics Data Report | 10% | 20th Nov 2014 |
| Final Examination | 30% | TBD |
Quantitative MS techniques
Due: 21st August
Weighting: 10%
From the primary literature discuss in an oral presentation (15min) an example of a quantitative MS technique, focused on the technical aspects and data generated.
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Molecular Graphics Structures
Due: 18th Sept 2014
Weighting: 10%
Students will produce a protein structure and animation using PyMOL software.
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Proteomics Data Report
Due: 26th Sept 2014
Weighting: 20%
- (7.5%) Students will be given a proteomic dataset from an iTRAQ expt. Use software tools to identify differentially expressed proteins. Carryout data mining and pathway analysis to demonstrate basic impact on cell biology.
- (12.5%) Students will be given a proteomic dataset from an MRM expt. Peak areas will be exported for use in Excel. Determine mean, S.D. and CV for each assay. Identify differentially expressed proteins amongst 2 groups.
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Process the datasets to give a broad overview of data in terms of size, quality and utility for further analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Genomics Data Presentation
Due: 24th Oct
Weighting: 20%
Students to be given two genome datasets. These are to be analysed following guidelines presented in the tutorials. The outcomes of these results are to be given as an Oral Presentation of 12min plus 3min question time.
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Process the datasets to give a broad overview of data in terms of size, quality and utility for further analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Glycomics Data Report
Due: 20th Nov 2014
Weighting: 10%
Students will be given a related glycomics and glycoproteomics dataset from LC-MS/MS analyses of purified human immunoglobulin (IgG). Use software tools to determine the monosaccharide composition of the carbohydrates (N-glycans) linked to IgG, their relative abundances and where they are linked to the IgG polypeptide backbone.
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Final Examination
Due: TBD
Weighting: 30%
Problem solving, essays and short answers
On successful completion you will be able to:
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Delivery and Resources
This unit uses team-based teaching in the form of 'lectorials' that encompass both lectures and hands-on experiences in data analysis. The tutors are actively involved in research activities to bring knowledge from real-world experiences in their respective fields. All tutorials take place on Thursday 2-6pm in F7B433 unless otherwise instructed. Tutorials will NOT be recorded. You must attend these tutorials to gain practical experience with data analysis. As some of the assessment is based on your practical use of specific software it is essential that you attend these classes.
It is expected that each student will bring to class a laptop PC computer to install data analysis software, or prior arrangements will be made with the convenor.
Students are encouraged to post and answer questions using the iLearn site.
Unit Schedule
|
Week |
Date |
Title |
Lecturer |
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Proteomics |
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1 |
Thurs 7th Aug |
Unit overview
Introduction to quantitative protein mass spectrometry techniques |
MM
MMcKay |
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2 |
Thurs 14th Aug |
Principles of quantitative experiment design and statistical analysis
Advanced MS workflows |
MM
MM, MMcKay |
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3 |
Thurs 21st Aug |
Pathway mapping and data mining |
DP, AG
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4 |
Thurs 28th Aug |
Targeted mass spectrometry (assay development, quantitation principles, SID, absolute quant) |
MMcKay
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5 |
Thurs 4th Sept |
Review targeted MS
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MMcKay
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Molecular Graphics for protein structure |
|||
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6 |
Thurs 11th Sept |
Introduction to PyMOL molecular graphics |
BM, BS |
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7 |
Thurs 18th Sept |
Molecular graphics II |
BM, BS |
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Mid-Semester Break 22 Sept-3rd Oct |
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Genomics |
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8 |
Thurs 9th Oct |
Genomics Introduction
Community Phylogenetics (16S amplicon) |
IP, SM |
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9 |
Thurs 16th Oct |
Review analysis of 16S amplicon data
Metagenomic sequencing |
IP, SM |
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10 |
Thurs 23rd Oct |
Review metagenomic analysis |
IP, SM |
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11 |
Thurs 30th Oct |
Oral Presentations |
IP, SM |
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Glycans and Glycoproteins |
|||
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12 |
Thurs 6th Nov |
Introductory Glycan and Glycoprotein analysis |
NP, MA |
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13 |
Thurs 13th Nov |
Glycan Databases and Analysis |
NP, MC |
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
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Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
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Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
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Graduate Capabilities
PG - Discipline Knowledge and Skills
Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Learning outcomes
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Process the datasets to give a broad overview of data in terms of size, quality and utility for further analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
Assessment tasks
- Quantitative MS techniques
- Molecular Graphics Structures
- Proteomics Data Report
- Genomics Data Presentation
- Glycomics Data Report
- Final Examination
PG - Critical, Analytical and Integrative Thinking
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
Learning outcomes
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Assessment tasks
- Quantitative MS techniques
- Molecular Graphics Structures
- Proteomics Data Report
- Genomics Data Presentation
- Glycomics Data Report
- Final Examination
PG - Research and Problem Solving Capability
Our postgraduates will be capable of systematic enquiry; able to use research skills to create new knowledge that can be applied to real world issues, or contribute to a field of study or practice to enhance society. They will be capable of creative questioning, problem finding and problem solving.
This graduate capability is supported by:
Learning outcomes
- Process the datasets to give a broad overview of data in terms of size, quality and utility for further analysis
- Learn how to analyze the dataset and compare it with established information about the system under investigation
Assessment tasks
- Molecular Graphics Structures
- Proteomics Data Report
- Genomics Data Presentation
- Glycomics Data Report
- Final Examination
PG - Effective Communication
Our postgraduates will be able to communicate effectively and convey their views to different social, cultural, and professional audiences. They will be able to use a variety of technologically supported media to communicate with empathy using a range of written, spoken or visual formats.
This graduate capability is supported by:
Learning outcomes
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Assessment tasks
- Quantitative MS techniques
- Proteomics Data Report
- Genomics Data Presentation
- Final Examination
PG - Engaged and Responsible, Active and Ethical Citizens
Our postgraduates will be ethically aware and capable of confident transformative action in relation to their professional responsibilities and the wider community. They will have a sense of connectedness with others and country and have a sense of mutual obligation. They will be able to appreciate the impact of their professional roles for social justice and inclusion related to national and global issues
This graduate capability is supported by:
Learning outcomes
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Assessment tasks
- Quantitative MS techniques
- Molecular Graphics Structures
- Proteomics Data Report
- Genomics Data Presentation
- Final Examination
PG - Capable of Professional and Personal Judgment and Initiative
Our postgraduates will demonstrate a high standard of discernment and common sense in their professional and personal judgment. They will have the ability to make informed choices and decisions that reflect both the nature of their professional work and their personal perspectives.
This graduate capability is supported by:
Learning outcomes
- Knowledge of appropriate techniques used in acquiring large biomolecular datasets and the limitations of the use of these methods
- Familiarisation with experiment design and critically assess the quality of large biomolecular datasets prior to in-depth analysis
- Demonstrate an ability to effectively report and draw new conclusions about a biomolecular system from analytical data
Assessment tasks
- Quantitative MS techniques
- Molecular Graphics Structures
- Proteomics Data Report
- Genomics Data Presentation
- Glycomics Data Report
- Final Examination