| layout | title | catalog | credits | semester | professor | office | phone | schedule | location | office_hours | office_hours_location | syllabus | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
page |
Syllabus |
BIOC 6820 |
3 |
Fall 2023 |
Dr. Peter R. Hoyt |
Room 110FC in the HBRC Building |
405-744-6206 |
10:30AM - 11:15AM T & Th |
ZOOM link TBD |
Tuesdays 10:30-11am |
110FC HBRC |
../docs/spring-2023-syllabus-attachment.pdf |
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Except for emergencies, Dr. Hoyt will only be available for virtual meetings in Fall 2022. Note: my schedule gets very busy during the semester so please try to schedule appointments as far in advance as possible. In general it will be very difficult to set up appointments less than 24 hours in advance.
The syllabus and other relevant class information and resources will be posted at the GitHub site. Changes to the schedule will be posted to this site so please try to check it periodically for updates.
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There is no required text book for this class.
Computers are increasingly essential to the study of all aspects of biology. The course seeks to improve cross-disciplinary understanding and will be taught using the Bash Shell, but the concepts learned will easily apply to all programming languages. No background in programming is required.
Knowledge of basic biology.
By the end of the course you will be able to use a BASH shell and bioinformatic tools to import data into proper formats for genomics, perform analysis on those data, and export the results to graphs, text files, and potentially databases.
Students completing this course will be able to:
- Write simple computer programs in the BASH shell
- Automate shell data analysis
- Create well structured dataframes*
- Extract information from dataframes*
- Apply these tools to address biological questions
This course contributes to the interdisciplinary techniques required to generate, analyze, and interpret complex biologically derived datasets as part of genomics by providing students the skills and knowledge they need to use bioinformatics tools in research.
This class is taught using active learner-centered approach, because learning to program and working with data requires actually interacting on computers. Self-motivation to learn the coding involved is required and often produces a better learning outcome.
Attendance will not be taken or factor into the grades for this class. Assignments will be due at the end of each week regardless of attendance. Keeping up with the assignments or exercises will mitigate your struggles to learn the material.
Weekly homework resembles quizzes but there will be no exams in this course.
Life happens and therefore there is an automatic grace period of 48 hours for the submission of late assignments with no need to request an extension. However, it is highly recommended that you submit assignments on time when possible because assignments build on one another and it can be hard to catch up if you fall behind. Reasonable requests for longer extensions will also be granted.
Assignments are due Saturday night by 11:59 pm Central Time. This allows you to be finished with one week's material before starting the next week's material. Assignments should be submitted via Canvas using the "quizzes" category. In emergencies, assignments can be submitted by email.
Students are required to provide their own laptops/desktops and to install free and open source software on those computers (see [Setup]({{ site.baseurl }}/computer-setup) for installation instructions). Support will be provided by the instructor in the installation of required software. If you need but don't have access to a suitable computer please contact an instructor and they will do their best to provide you with one.
Students requesting accommodation for disabilities must first register with the Student Disability office. The Dean of Students Office will provide documentation to the student who must then provide this documentation to the instructor when requesting accommodation. You must submit this documentation prior to submitting assignments or taking the quizzes or exams. Accommodations are not retroactive, therefore, students should contact the office as soon as possible in the term for which they are seeking accommodations.
Academic honesty and integrity are fundamental values of the University community. Students should be sure that they understand the OSU Acedemic Integrity Code at https://academicintegrity.okstate.edu/content/academic-integrity-resources.
All members of the class are expected to follow rules of common courtesy in all email messages, threaded discussions and chats. For guidance please read the Carpentries Code of Conduct
- Counseling and Wellness resources
- Disability resources
- Resources for handling student concerns and complaints
- OSU IT Helpdesk support
- Additional OSU Policies
Most importantly, if you are struggling for any reason please come talk to the instructor and I will do my best to help.
Grading for this course is tentatively based on 13 assignments. Some assignments (as needed) will receive a thorough review and a detailed grade. Other problems will be graded as follows:
- Produces the correct answer using the requested approach: 100%
- Generally uses the right approach, but a minor mistake results in an incorrect answer: 90%
- Attempts to solve the problem and makes some progress using the core concept: 50%
- Answer demonstrates a lack of understanding of the core concept: 0%
- A 93-100
- A- 90-92
- B+ 87-89
- B 83-86
- B- 80-82
- C+ 77-79
- C 73-76
- C- 70-72
- D+ 67-69
- D 60-66
- F <60
The details of the course schedule are available on the course website: [schedule]({{ site.baseurl }}/schedule).
Disclaimer: This syllabus represents our current plans and objectives. As we go through the semester, those plans may need to change. Such changes will be communicated clearly both on the website and in class.
* Dataframes in this context includes tabular data