Bioinformatics
(BGGN 213, Winter 2023)

Course Director: Prof. Barry J. Grant (Email: bjgrant@ucsd.edu)
Instructional Assistant: Eva (Yu) Zhang (Email: yuz098@ucsd.edu)
Course Syllabus: Winter 2023 (PDF)

COVID-19: At the time of writing we are still in a major COVID-19 pandemic crisis. Whilst we are making every effort to support your learning in a safe in-person environment, we expect and require your help. Keeping our classroom community healthy takes all of us following campus safety requirements. You are expected to follow University public health requirements and pursue personal protection practices to protect yourself and the others around you from infection. These include:

Participating in the university’s daily screening process. Everyone must complete a Daily Symptom Screener.
Participating in the university's testing program. All students are required to participate in the COVID-19 Testing program in accordance with their vaccination status.
Wear a well-fitting mask that covers your nose and mouth at all times. Everyone is required to wear masks indoors regardless of vaccination status. If you see someone not wearing a mask, or wearing it incorrectly, kindly ask them to mask up. If you have concerns please bring them to my attention.
Monitor potential exposures and comply with contact tracing efforts. Look out for the daily updates and potential exposure list that the university sends out with building information and the dates of exposure.
Stay home if you’re feeling ill! If you’re not feeling well, complete the symptom screener and if needed, get tested for COVID-19. Do not come to campus unless given the all-clear. When you are able please contact me and I will make every effort to support your continued learning. We are all susceptible to COVID-19 illness-related disruptions and I have designed this course with pandemic resilience in mind.

I will do everything possible to help ensure that instruction is as safe as possible. This means that if conditions change and in-person instruction is no longer deemed as safe as it could be by the University and public health officials, we will pivot immediately to remote teaching. My hope is that this course can remain in-person and regardless of delivery mode serve as a venue where we build a vibrant supportive learning community. The following UCSD website has many useful resources on returning to in-person learning.

Overview

Bioinformatics - the application of computational and analytical methods to biological problems - is a rapidly maturing field that is driving the collection, analysis, and interpretation of the avalanche of data in modern life sciences and medical research.

This course is designed for bioscience graduate students and provides a hands-on introduction to the computer-based analysis of genomic and biomolecular data.

Major topics include:

Genomic and biomolecular bioinformatic resources,
Genome informatics,
Structural informatics,
Transcriptomics,
UNIX for bioinformatics, and
Bioinformatics data analysis with R.

A detailed listing of all course topics is available and includes a guest lecture from a genomic scientist at Illumina Inc., Synthetic Genomics Inc., Human Longevity Inc., or the La Jolla Institute for Allergy and Immunology subject to student voting preferences.

Students completing this course will be able to evaluate new genomic and biomolecular information using existing software and gain experience in combining bioinformatic approaches to answer specific biological questions. Our broader goal is to point towards perspectives that bioinformatics can expose for the integration and analysis of complex biological information. For further details please see our complete list of course objectives and specific learning goals.

Audience:

Bioscience graduate students and others familiar with basic molecular biology concepts. No formal programming training or high level mathematical skills are required.

Accessibility:

We are committed to making this course accessible to everybody. Please contact Prof. Grant bjgrant@ucsd.edu if you have questions regarding room accessibility.

Requirements:

To fully participate in this course students will be expected to use their own laptop computers with specific freely available software installed. A limited number of classroom computers are also available should the need arise.

Schedule:

N.B. This quarter, BGGN-213 will be offered in-person only on Wednesday and Friday at 1:00 - 4:00 pm in TATA 2501 (Map). Additional video lectures, screencast lab review sessions and supporting material will be available via this website on a weekly basis throughout the quarter. A detailed schedule with class related material is provided online.

Class announcements:

All announcements regarding the course will be by email to your UCSD address. We will also be using Piazza to facilitate course communication, particularly around questions and answers. If you have a question outside of class or office hours, first check if it has already been asked on Piazza and if not post there. If you have a question or concern you don’t feel comfortable posting on Piazza feel free to reach out via email.

Office hours:

We will use Zoom on a weekly basis at a time to be determined from student polling. For now email me for a time and we will make it happen.

Textbook:

There is no textbook for the course. Lecture notes, homework assignments, grading criteria, pre-class screen casts and required reading material will be available from this public facing course website.

Syllabus:

A detailed syllabus with topic outlines and learning goals is available for download.

Surveys:

Please help us improve this course by completing by completing these surveys before and after the course. Thank you!

Acknowledgments:

In addition to working on personal laptops we will also be using remote supercomputing resources for analyzing bioinformatics data at scale. Our use of these resources is kindly supported by NSF/XSEDE grant allocation TG-BIO170077.

To further support learning data analysis with the R environment we gratefully acknowledge support from DataCamp. DataCamp are providing our enrolled students with access to over 300 hours of data science videos and interactive coding challenges aimed at strengthening their data science skills.

Additional key resources

Key resources for students in this class include:

Piazza our main Q&A forum.
GradeScope for assignment and lab report submission and grading.
GradeBook check your assignment and lab scores to date.
Schedule complete listing of class related material.
Syllabus PDF format guide to the course.

Note that these resources are also linked to at the bottom of the navigation sidebar found on every page via the Q&A, GradeScope, YouTube and email icons.

Selected screencast videos

These short (sub 10 minute) videos are available for students to watch before class and are designed to help address potential variability in student background knowledge and aid with class inclusivity.