Education and Outreach

Spring 2017-2020 | Computational Immunology Mini Course

This course provides an overview of computational methods used in the analysis of immunological data, including transcriptomics, next generation sequencing, cytometry and CyTOF. We provide a theoretical framework but focus on real applications.

The first hour of each session is in lecture format (livestreamed and archived) followed by an intimate discussion session with the registered students.

  • Spring 2020 (COVID-19 focus): Co-directed by Marina Sirota, Gabi Fragiadakis and Matt Spitzer.
  • Spring 2019: Co-directed by Marina Sirota, Jill Hollenbach and Matt Spitzer.
  • Spring 2018: Co-directed by Marina Sirota, Jill Hollenbach and Matt Spitzer
  • Spring 2017: Co-directed by Marina Sirota, Matt Spitzer.

Effective modeling, acquisition and mining of data have become crucial for solving important problems in immunology.  This course explores novel molecular and computational approaches to interrogating outstanding questions in immunology and related fields. We will provide an overview of computational methods used in the analysis of immunological data, including transcriptomics, next generation sequencing, microbiome, immune repertoire, cytometry and CyTOF. Speakers are invited to share their insights into the state-of-the-art trends, provide a theoretical framework but also focus on real applications. Please find links to some relevant lectures below.

Analysis of Gene Expression Data – Marina Sirota [video]

Gene Expression Meta-Analysis – Purvesh Khatri [video]

Analysis of Single Cell RNASeq – Dvir Aran [video]

Analysis if Genetics and HLA Data – Jill Hollenbach [video]

Analysis of CYTOF Data – Mathew Spitzer [video]

Analysis of Microbiome Data – Patrick Bradley [video]

Analysis of Immune Repertoire – Michael Wilson [video]

Summer 2016 | Computational Immunology Seminars

A Computational Immunology Seminar Series offered in collaboration with Stanford University. Seminars hosted at Stanford and interactively streamed at UCSF in Mission Hall. 


Summer 2019-2020 | UCSF AI4ALL Program

UCSF AI4ALL is a partnership between UCSF and AI4ALL to teach AI to high school students from underrepresented groups, focusing on AI for biomedical applications. Founded and directed by Marina Sirota and co-directed by Tomiko Oskotsky, this tuition-free annual program involves hands-on experience with AI, hearing from a diverse set of role models in AI, and learning about how AI can be used to advance health. Please donate to UCSF AI4ALL!


Data Science CoLab Workshops and Resources

Virtual Office Hours: (Tuesdays 2-4pm) by appointment. We will add additional windows as needed.

For an appointment email us at [email protected]


During non-shutdown: We offer Office Hours in lab space in S-824 in the Medical Science Building at Parnassus every Tuesday from 2-4pm. 


If you plan to come, please email us with some background on your project, data types, and questions before you stop by. 


Other Resources: 


Ask an expert at the Data Science Initiative through the UCSF Library 


Email The Gladstone Bioinformatics Core.


Recorded workshops:


Introduction to R workshop by Arjun Rao , based on materials from the Gladstone

Introduction to Single-cell Analysis by Arjun Rao

Introduction to Python by Arjun Rao