Bioinformatics Lab
(BIMM 143, Spring 2023)

Course Instructor: Dr. Marcos Díaz-Gay (Email: mdiazgay@ucsd.edu)
Instructional Assistant: Josef Reimon Rodriguez Urrete (Email: jurrete@ucsd.edu)
Course Syllabus: Spring 2023 (PDF)
Course Materials: Prof. Barry J. Grant

COVID-19: At the time of writing, we are still in a major COVID-19 pandemic crisis. While 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 can benefit from the COVID-19 Testing program in accordance with their vaccination status.
Wearing a well-fitting mask that covers your nose and mouth if you have been exposed to COVID-19 or are having symptoms but test negative, according to the current campus recommendations. I encourage anyone who feels more comfortable continuing to wear a mask to do so, as masking remains one of the easiest and most effective ways to reduce the spread of the virus.
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 can be defined as the application of computational and analytical methods to complex biological problems. Bioinformatics 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 upper division 4-unit course is designed for biology majors and introduces the principles and practical approaches of bioinformatics as applied to genes and proteins.

An integrated lecture/lab structure with hands-on exercises and small-scale projects emphasizes modern developments in genomics and proteomics. A detailed listing of all lecture topics is available and includes the major areas of:

Genomic and biomolecular bioinformatic resources
Advances in sequencing technologies
Genome informatics
Structural informatics
Transcriptomics
Bioinformatics data analysis with R

By completing this course, you will be able to apply leading existing bioinformatics tools to address complex 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

Biology majors with upper division standing. Familiarity with basic biomedical concepts is essential (students should have completed BILD 1 and BILD 4 or BIMM 101). No formal programming training or high-level mathematical skills are required.

Accessibility

We are committed to making this course accessible to everybody. Please contact Dr. Díaz-Gay mdiazgay@ucsd.edu if you have questions regarding content accessibility.

Requirements

To fully participate in this course students will be expected to use their own computers with specific freely available software installed.

Schedule

For the Spring 2023 quarter, BIMM 143 will be offered in-person only on Wednesdays and Fridays at 12 - 3 pm in YORK 3050 (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.

Office hours

In-person and Zoom-based office hours will be available on a weekly basis. Marcos office hours are in-person after class on Fridays (3pm) and on Zoom on Mondays at 12pm (link). Josef office hours are on Zoom on Mondays at 4pm (link).

Office hours are a time when you can come ask clarifying questions about the course material, chat about research, career goals, or about any other topics!

Class announcements and communication

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 it there. If you have a question or concern you don’t feel comfortable posting on Piazza, feel free to reach out via email (mdiazgay@ucsd.edu).

Textbook

There is no textbook for the course. Lecture notes, homework assignments, grading criteria, video lectures, hands-on session screencasts 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:

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 Piazza 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.