BIOSCI 700 : Phylogenetics
2023 Semester One (1233) (15 POINTS)
Capabilities Developed in this Course
|Capability 1:||Disciplinary Knowledge and Practice|
|Capability 2:||Critical Thinking|
|Capability 3:||Solution Seeking|
|Capability 4:||Communication and Engagement|
|Capability 5:||Independence and Integrity|
- Describe the application of computational methods to the inference of pairwise and multiple sequence alignments and, hence, of positional homology (Capability 1)
- Write scripts in R that implement some of the principle algorithms used in comparative bioinformatics and phylogenetics. (Capability 3)
- Describe the design and operation of Markov models and understand how they may be applied in sequence alignment, and for modelling sequence evolution and phylogenetic relationships. (Capability 1)
- Criticially evaluate the models and methods to perform comparative analysis of biological data (Capability 2)
- Explain the commonalities and differences between Maximum Likelihood versus Bayesian inference. (Capability 1)
- Apply various methods for maximising the likelihood (analytic versus numerical), and their advantages/disadvantages. (Capability 1)
- Describe various methods for penalizing likelihood based on model complexity (LRT, AIC, AICc, BIC; or Bayes Factors in a Bayesian context), and their assumptions and advantages/disadvantages (Capability 1 and 2)
- Design, implement, and explain an analysis of macroevolutionary data using R (Capability 3, 4 and 5)
|Final Exam||40%||Individual Coursework|
|Assessment Type||Learning Outcome Addressed|
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This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.
For this course, you can expect 3 hours of lectures/discussions per week, a 3 hour tutorial every 2 weeks, 3 hours of reading and thinking about the content and 3 hours of work on assignments and/or test preparation.
This course is designated a "campus experience," meaning:
- Attendance is expected at scheduled activities including labs/tutorials to complete components of the course.
- Lectures will be available as recordings. Other learning activities including labs will not be available as recordings.
- The course will not include live online events.
- The activities for the course are scheduled as a standard weekly timetable.
Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).
Please remember that the recording of any class on a personal device requires the permission of the instructor.
Health & Safety
The labs are computer labs that can be done online in the event of a University-mandated lockdown. No special safety issues with this course.
During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.
At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.
Your feedback helps to improve the course and its delivery for all students.
Students are encouraged to submit SET reviews to provide feedback on the course.
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If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.
If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.
This should be done as soon as possible and no later than seven days after the affected test or exam date.
In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.
The delivery mode may change depending on COVID restrictions. Any changes will be communicated through Canvas.
Student Charter and Responsibilities
The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.
Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.
In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.