Quantitative biology and bioinformatics demand a combination of technical skills and domain knowledge. In these data-driven sciences, effective communication with experimentalists is a prerequisite to success, as both parties must comprehend both the problem and the solution. In this course, students will gain consulting experience in quantitative biology and bioinformatics. They will learn to communicate effectively with clients, both verbally and in writing, and how to avoid jargon without sacrificing precision. Students will interact with experimentalists and learn to distil biological goals and challenges into quantitative/computational problems to be solved. Students will gain experience collaborating and solving these problems in a mentored professional setting. In doing so, they will learn how to report on their progress to both clients and colleagues.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Communicate effectively and professionally with scientists outside of their discipline
- Translate biological goals and challenges into underpinning quantitative/computational problems
- Engage in an independent investigation and evaluation of quantitative/computational solutions to biological problems
- Describe and defend a chosen methodology in the context of the problem being solved
- Estimate the difficulty of a project and the time commitment that will be required
- Identify when additional skills and/or expertise will be required to solve a problem
Research-Led Teaching
This course builds quantitative and computational skills that are often prerequisite to the prosecution of modern biological research. Key aspects include the development of statistical thinking, the translation of a biological research problem into a cognate data science challenge and the building of skills to address that challenge. Most assignments will use authentic data from biological research projects. The summative project with involve the replication of published results from published data.
Required Resources
Students must have access to a computer
Staff Feedback
Students will be given feedback in the following forms in this course:
- written comments
- verbal comments
- feedback to whole class, groups, individuals, focus group etc
Student Feedback
ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.
Class Schedule
Week/Session | Summary of Activities | Assessment |
---|---|---|
1 | Introduction to R and data manipulation | Weekly assignment |
2 | Data visualisation and the analysis workflow | Weekly assignment |
3 | Introduction to statistical thinking, linear models with one factor | Weekly assignment |
4 | Linear models with multiple factors. | Weekly assignment |
5 | Linear mixed models | Weekly assignment |
6 | Generalised linear models | Weekly assignment |
7 | Generalised linear models (continued) | Weekly assignment |
8 | Experimental design | Weekly assignment |
9 | Generalised linear mixed models | Weekly assignment |
10 | High-dimensional data analysis | Weekly assignment |
11 | Applications to biological experiments | |
12 | Applications to biological experiments | Project |
Assessment Summary
Assessment task | Value | Due Date | Return of assessment | Learning Outcomes |
---|---|---|---|---|
Weekly assignments (1/10) | 7 % | 05/08/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (2/10) | 7 % | 12/08/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (3/10) | 7 % | 19/08/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (4/10) | 7 % | 26/08/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (5/10) | 7 % | 02/09/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (6/10) | 7 % | 09/09/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (7/10) | 7 % | 30/09/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (8/10) | 7 % | 07/10/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (9/10) | 7 % | 14/10/2020 | * | 1,2,3,4,5,6 |
Weekly assignments (10/10) | 7 % | 21/10/2020 | * | 1,2,3,4,5,6 |
Project | 30 % | 26/10/2020 | 05/11/2020 | 1,2,3,4,5,6 |
* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details
Policies
ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:
- Student Assessment (Coursework) Policy and Procedure
- Special Assessment Consideration Policy and General Information
- Student Surveys and Evaluations
- Deferred Examinations
- Student Complaint Resolution Policy and Procedure
Assessment Requirements
The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Integrity . In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.
Moderation of Assessment
Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.
Participation
This course is run as a workshop and active participation is expected when technology and circumstances allow.
Assessment Task 1
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (1/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 2
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (2/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 3
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (3/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 4
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (4/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 5
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (5/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 6
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (6/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 7
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (7/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 8
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (8/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 9
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (9/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 10
Learning Outcomes: 1,2,3,4,5,6
Weekly assignments (10/10)
This course is designed to progressively build knowledge and skills. Each of Weeks 1-10 has a topical focus to be introduced on Thursday (1 hr) and developed further on Friday (2 hr). On Friday, students will be assigned a coding and comprehension task that reinforces and extends that week's material. These assignments will be due Wednesday of the following week.
Assessment Task 11
Learning Outcomes: 1,2,3,4,5,6
Project
The summative task for this course is a project for which the students will work alone or in pairs to interrogate and replicate the results of a research paper using its published data. Students may commence their project as soon as they are ready, likely early in the second half of the semester. The project is due online in Wattle on Monday of
Week 12.
Academic Integrity
Academic integrity is a core part of the ANU culture as a community of scholars. At its heart, academic integrity is about behaving ethically, committing to honest and responsible scholarly practice and upholding these values with respect and fairness.
The ANU commits to assisting all members of our community to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to be familiar with the academic integrity principle and Academic Misconduct Rule, uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with.
The Academic Misconduct Rule is in place to promote academic integrity and manage academic misconduct. Very minor breaches of the academic integrity principle may result in a reduction of marks of up to 10% of the total marks available for the assessment. The ANU offers a number of online and in person services to assist students with their assignments, examinations, and other learning activities. Visit the Academic Skills website for more information about academic integrity, your responsibilities and for assistance with your assignments, writing skills and study.
Online Submission
You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.
Hardcopy Submission
For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.
Late Submission
Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.
Referencing Requirements
Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.
Returning Assignments
Assignments will be returned?via Wattle
Extensions and Penalties
Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.
Resubmission of Assignments
Resubmission of assignments is not only permitted but encouraged. The goal is to master the material and the instructors welcome repeated efforts when required.
Privacy Notice
The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.
Distribution of grades policy
Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.
Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.
Support for students
The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).
- ANU Health, safety & wellbeing for medical services, counselling, mental health and spiritual support
- ANU Diversity and inclusion for students with a disability or ongoing or chronic illness
- ANU Dean of Students for confidential, impartial advice and help to resolve problems between students and the academic or administrative areas of the University
- ANU Academic Skills and Learning Centre supports you make your own decisions about how you learn and manage your workload.
- ANU Counselling Centre promotes, supports and enhances mental health and wellbeing within the University student community.
- ANUSA supports and represents undergraduate and ANU College students
- PARSA supports and represents postgraduate and research students
Convener
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Prof Eric Stone
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Instructor
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Prof Eric Stone
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Instructor
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Dr Robert Cope
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Instructor
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Dr Teresa Neeman
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Instructor
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Dr Timothee Bonnet
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