Course Structure

Through this course graduate students are eligible to receive credits for successfully completing the QCB Collaboratory Workshops.

Workshops are offered quarterly with the exception of summer. Each workshop runs for 2-3 days, 2-3 hours per day, and are held weekly. Attendance is mandatory for all days.

**Starting in Spring 2020**

To receive course credit, students must complete least 3 workshops taught during quarter, complete the quiz with a passing grade, and enroll in 275A and/or B, respectively. To receive credit for both 275A and 275B, students must complete a total of 6 workshops taught during the quarter, and complete the quiz with a passing grade. If the course if full please request a PTE by emailing collaboratory@ucla.edu

Course Description

Bioinformatics 275A, 2 units

This lab course introduces graduate students to contemporary methods and techniques in bioinformatics that are used to analyze high-throughput genomic data. Workshops of one week each are offered throughout the grading period. Students select and complete three workshops taught during the quarter, based on topics most relevant to their own research. Workshop topics include Introduction to the Unix command line, NGS data analysis, R Programming, BS-Seq, and many others.

Bioinformatics 275B, 2 units

This lab course exposes graduate students to contemporary methods and techniques in bioinformatics that are used to analyze high-throughput genomic data. Workshops of one week each on are offered throughout the grading period. Students select and complete three workshops taught during the quarter, based on topics most relevant to their own research. Workshop topics include RNA, Python, Machine Learning, and Variant Calling.

For a complete list of workshops, click here: https://qcb.ucla.edu/collaboratory/schedule-of-workshops/

Grading

**Starting in Spring 2020***

How Your Learning Will Be Assessed (Grading Policy)

The final grade will be determined by participation (50%) and the final exam (50%).

Why I do not grade on a curve: In recent years, research into higher education assessment practices have shown that grading on a curve can create unnecessarily competitive environments for students and result in outcomes that disadvantage some groups of students over others. This is true in data collected and analyzed for our students at UCLA as well. For this reason, I do not grade on a curve. Your grade is therefore not based on how you did in comparison to your peers, but instead how successful you are at evidencing that you have mastered the intended learning goals for that specific assessment. However, if I do find that particular assessment questions I gave an assignment or exam were unreasonably challenging, unclear, or unfair for any reason I will  provide additional credit as appropriate. If you ever feel that an assignment or specific question is unfair or confusing please come and speak with me or your TA (ideally before it is due or during the assessment, but afterwards is okay also) so that we can address this concern as soon as possible. I am committed to making sure the assessment of your learning is comprehensive, fair, and incorporates best practices from education research on assessment design and inclusive practices.

Grading Scale: (Modify as appropriate)

Letter Grade Percentage
A+ 99-100%
A 93%-98.9%
A- 90%-92.9%
B+ 87%-89.9%
B 83%-86.9%
B- 80%-82.9%
C+ 77%-79.9%
C 73%-76.9%
C- 70%-72.9%
D 60%-69.9%
F 0%-59%


Applied Bioinformatics Lab Syllabus

For the M275A and M275B Syllabus – Spring 2020 quarter, please click M275AB Spring 2020.

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